@proceedings {989, title = {Impact of free-water correction on white matter changes measured by diffusion tensor imaging in migraine}, volume = {4601}, year = {2023}, month = {2023}, abstract = {

Menstrual migraine affects about 25\% of female migraine patients. However, the diagnosis of migraine is particularly difficult because the brain changes associated with migraine are challenging to detect with imaging techniques. Diffusion-weighted MRI (dMRI) permits the detection of alterations in the microenvironment of the brain tissues. We investigate whether removing the contribution of the free water component from the diffusion-signal can provide increased sensitivity to identify white matter changes in migraine using diffusion tensor metrics.

}, author = {Guadilla, Irene and Fouto, Ana and {\'A}lvaro Planchuelo-G{\'o}mez and Trist{\'a}n-Vega, Antonio and Ruiz-Tagle, Amparo and Esteves, In{\^e}s and Caetano, Gina and Silva, Nuno and Vilela, Pedro and Gil-Gouveia, Raquel and Aja-Fern{\'a}ndez, Santiago and Figueiredo, Patr{\'\i}cia and Nunes, Rita} } @proceedings {987, title = {Super-resolution diffusion tensor imaging at 64 mT}, volume = {3624}, year = {2023}, month = {2023}, abstract = {

A super-resolution approach was used to create 2mm isotropic diffusion tensor images (DTI) from diffusion-weighted imaging data acquired on a low field, portable system. Mean diffusivity, fractional anisotropy and principal eigenvector orientation maps are shown. This work extends the very recently implemented capability of performing DTI on a 64mT system, and shows substantial improvement due to the increased through-plane resolution achieved with super-resolution.

}, author = {Plumley, Alix and Cercignani, Mara and {\'A}lvaro Planchuelo-G{\'o}mez and Gholam, James and Jones, Derek K} } @proceedings {984, title = {Tensors and Tracts at 64 mT}, volume = {104}, year = {2023}, month = {2023}, abstract = {

We present the first ever demonstration of Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) including quantitative measures of mean diffusivity, fractional anisotropy, and successful tractographic reconstruction of projection and commissural pathways on a portable system operating at 64 mT.

}, author = {Plumley, Alix and Padormo, Francesco and Cercignani, Mara and O{\textquoteright}Halloran, Rafael and Teixeira, Rui and {\'A}lvaro Planchuelo-G{\'o}mez and Legouhy, Antoine and Luo, Tianrui and Jones, Derek K} } @proceedings {985, title = {Validation of Deep Learning techniques for quality augmentation in diffusion MRI for clinical studies}, volume = {2786}, year = {2023}, month = {2023}, abstract = {

This work gathers the results of the QuadD22 challenge, held in MICCAI 2022. We evaluate whether Deep Learning (DL) Techniques are able to improve the quality of diffusion MRI data in clinical studies. To that end, we focused on a real study on migraine, where the differences between groups are drastically reduced when using 21 gradient directions instead of 61. Thus, we asked the participants to augment dMRI data acquired with only 21 directions to 61 via DL. The results were evaluated using a real clinical study with TBSS in which we statistically compared episodic migraine to chronic migraine.

}, author = {Aja-Fernandez, Santiago and Martin-Martin, Carmen and Pieciak, Tomasz and {\'A}lvaro Planchuelo-G{\'o}mez and Faiyaz, Abrar and Uddin, Nasir and Tiwari, Abhishek and Shigwan, Saurabh J and Zheng, Tianshu and Cao, Zuozhen and Blumberg, Stefano B and Sen, Snigdha and Yigit Avci, Mehmet and Li, Zihan and Wang, Xinyi and Tang, Zihao and Rauland, Amelie and Merhof, Dorit and Manzano Maria, Renata and Campos, Vinicius P and HashemiazadehKolowri, SeyyedKazem and DiBella, Edward and Peng, Chenxu and Chen, Zan and Ullah, Irfan and Mani, Merry and Eckstrom, Samuel and Baete, Steven H and Scifitto, Scifitto and Singh, Rajeev Kumar and Wu, Dan and Goodwin-Allcock, Tobias and Slator, Paddy J and Bilgic, Berkin and Tian, Qiyuan and Cabezas, Mariano and Santini, Tales and Andrade da Costa Vieira, Marcelo and Shen, Zhimin and Abdolmotalleby, Hesam and Filipiak, Patryk and Tristan-Vega, Antonio and de Luis-Garcia, Rodrigo} } @article {995, title = {Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies}, journal = {NeuroImage: Clinical}, volume = {39}, year = {2023}, pages = {103483}, abstract = {

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clinical applications. The study aims to determine whether the use of artificial intelligence (AI) methods in medical images may result in the loss of critical clinical information and/or the appearance of false information. To assess this, the focus was on the angular resolution of dMRI and a clinical trial was conducted on migraine, specifically between episodic and chronic migraine patients. The number of gradient directions had an impact on white matter analysis results, with statistically significant differences between groups being drastically reduced when using 21 gradient directions instead of the original 61. Fourteen teams from different institutions were tasked to use DL to enhance three diffusion metrics (FA, AD and MD) calculated from data acquired with 21 gradient directions and a b-value of 1000 s/mm2. The goal was to produce results that were comparable to those calculated from 61 gradient directions. The results were evaluated using both standard image quality metrics and Tract-Based Spatial Statistics (TBSS) to compare episodic and chronic migraine patients. The study results suggest that while most DL techniques improved the ability to detect statistical differences between groups, they also led to an increase in false positive. The results showed that there was a constant growth rate of false positives linearly proportional to the new true positives, which highlights the risk of generalization of AI-based tasks when assessing diverse clinical cohorts and training using data from a single group. The methods also showed divergent performance when replicating the original distribution of the data and some exhibited significant bias. In conclusion, extreme caution should be exercised when using AI methods for harmonization or synthesis in clinical studies when processing heterogeneous data in clinical studies, as important information may be altered, even when global metrics such as structural similarity or peak signal-to-noise ratio appear to suggest otherwise.

}, keywords = {Angular resolution, Artificial Intelligence, Deep learning, Diffusion tensor, diffusion MRI, machine learning}, issn = {2213-1582}, doi = {https://doi.org/10.1016/j.nicl.2023.103483}, url = {https://www.sciencedirect.com/science/article/pii/S2213158223001742}, author = {Santiago Aja-Fern{\'a}ndez and Carmen Mart{\'\i}n-Mart{\'\i}n and {\'A}lvaro Planchuelo-G{\'o}mez and Abrar Faiyaz and Md Nasir Uddin and Giovanni Schifitto and Abhishek Tiwari and Saurabh J. Shigwan and Rajeev Kumar Singh and Tianshu Zheng and Zuozhen Cao and Dan Wu and Stefano B. Blumberg and Snigdha Sen and Tobias Goodwin-Allcock and Paddy J. Slator and Mehmet Yigit Avci and Zihan Li and Berkin Bilgic and Qiyuan Tian and Xinyi Wang and Zihao Tang and Mariano Cabezas and Amelie Rauland and Dorit Merhof and Renata Manzano Maria and Vin{\'\i}cius Paran{\'\i}ba Campos and Tales Santini and Marcelo Andrade da Costa Vieira and SeyyedKazem HashemizadehKolowri and Edward DiBella and Chenxu Peng and Zhimin Shen and Zan Chen and Irfan Ullah and Merry Mani and Hesam Abdolmotalleby and Samuel Eckstrom and Steven H. Baete and Patryk Filipiak and Tanxin Dong and Qiuyun Fan and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Tomasz Pieciak} } @conference {975, title = {Comparing signal models for correcting diffusion-weighted MR images for free water partial volume effects}, booktitle = {ISMRM Workshop on Diffusion MRI: From Research to Clinic}, year = {2022}, address = {Amsterdam, The Netherlands}, author = {Guadilla, Irene and Fouto, Ana R. and {\'A}lvaro Planchuelo-G{\'o}mez and Trist{\'a}n-Vega, Antonio and Ruiz-Tagle, Amparo and Esteves, In{\^e}s and Caetano, Gina and Aja-Fern{\'a}ndez, Santiago and Figueiredo, Patr{\'\i}cia and Nunes, Rita G.} } @conference {967, title = {Objective measurement of pain related to cardiac surgery: a study using algometry}, booktitle = {8th Congress of the European Academy of Neurology}, year = {2022}, month = {2022}, abstract = {

Background and aims: Algometry is a safe and objective technique to quantify pain, up to now used in headache research, but to a lesser extent to assess pain related to surgery. We aimed to analyze the demographic characteristics of pain related to cardiac surgery, assessed using static algometry.

Methods: Adult patients consecutively undergoing cardiac surgery were prospectively recruited. Pressure pain thresholds (PPT) were measured in both sides of sternum manubrium, body (five measures) and xiphoid process, preoperatively and on days 1, 3 and 7 postoperatively. Linear mixed-effects models were employed to assess the longitudinal changes and results were corrected for multiple comparisons following a false discovery rate procedure.

Results: We included 70 patients (41.4\% female) with a median age of 67.5 years (range 26-85). Regarding the baseline values, PPT were significantly lower in women and patients older than 65 years. After the surgery, there was a significant reduction of PPT in all assessed regions, which was partially compensated after seven days. Moreover, postoperatively, differences associated with age disappeared and those associated with sex were almost negligible. These differences related to age and sex increased after seven days of surgery, but this difference was lower in comparison with the baseline situation (Table 1, Figure 1). Postoperative pain perception was significantly higher (lower PPT) in both sexes.

Conclusion: Pain related to cardiac surgery can be measured with algometry, mainly during first postoperative days. Differences in pain sensitivity related to age and sex decrease after surgery.

Disclosure: No conflict of interest.

}, author = {Segura-M{\'e}ndez, B{\'a}rbara and {\'A}lvaro Planchuelo-G{\'o}mez and Sierra, {\'A}lvaro and Garc{\'\i}a-Azor{\'\i}n, David and Velasco-Garc{\'\i}a, E. and Fuentes-Mart{\'\i}n, {\'A}. and S{\'a}nchez, C. and V{\'a}zquez-Alarc{\'o}n de la Lastra, I. and {\'A}ngel L. Guerrero and Carrascal, Yolanda} } @article {957, title = {Perceived quality of life (QOLIE-31-P), depression (NDDI-E), anxiety (GAD-7), and insomnia in patients with epilepsy attended at a refractory epilepsy unit in real-life clinical practice}, journal = {Neurological Sciences}, volume = {43}, year = {2022}, month = {2022}, pages = {1955-1964}, doi = {https://doi.org/10.1007/s10072-021-05595-3}, url = {https://link.springer.com/article/10.1007/s10072-021-05595-3}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and Vieira Campos, Alba and Mart{\'\i}nez-Dubarbie, Francisco and Vivancos, Jos{\'e} and De Toledo-Heras, Mar{\'\i}a} } @article {963, title = {Synthetic MRI improves radiomics-based glioblastoma survival prediction}, journal = {NMR in Biomedicine}, year = {2022}, chapter = {e4754}, doi = {10.1002/nbm.4754}, author = {Elisa Moya-S{\'a}ez and Rafael Navarro-Gonz{\'a}lez and Santiago Cepeda and {\'A}ngel P{\'e}rez-N{\'u}{\~n}ez and Rodrigo de Luis-Garcia and Santiago Aja-Fernández and Carlos Alberola-L{\'o}pez} } @conference {976, title = {Tensors and Tracts at 64 mT}, booktitle = {ISMRM Workshop on Diffusion MRI: From Research to Clinic}, year = {2022}, address = {Amsterdam, The Netherlands}, author = {Plumley, Alix and Padormo, Francesco and Cercignani, Mara and O{\textquoteright}Halloran, Rafael and Teixeira, Rui and {\'A}lvaro Planchuelo-G{\'o}mez and Legouhy, Antoine and Luo, Tianrui and Jones, Derek K.} } @article {960, title = {Fast 4D elastic group-wise image registration. Convolutional interpolation revisited}, journal = {Computer Methods and Programs in Biomedicine}, volume = {200}, year = {2021}, pages = {105812}, abstract = {

Background and Objective:This paper proposes a new and highly efficient implementation of 3D+t groupwise registration based on the free-form deformation paradigm. Methods:Deformation is posed as a cascade of 1D convolutions, achieving great reduction in execution time for evaluation of transformations and gradients. Results:The proposed method has been applied to 4D cardiac MRI and 4D thoracic CT monomodal datasets. Results show an average runtime reduction above 90\%, both in CPU and GPU executions, compared with the classical tensor product formulation. Conclusions:Our implementation, although fully developed for the metric sum of squared differences, can be extended to other metrics and its adaptation to multiresolution strategies is straightforward. Therefore, it can be extremely useful to speed up image registration procedures in different applications where high dimensional data are involved.

}, keywords = {B-splines, Convolution, Efficient implementation, Free-form deformation, Groupwise Registration, Non-rigid registration}, issn = {0169-2607}, doi = {https://doi.org/10.1016/j.cmpb.2020.105812}, url = {https://www.sciencedirect.com/science/article/pii/S016926072031645X}, author = {Rosa-Mar{\'\i}a Mench{\'o}n-Lara and Javier Royuela-del-Val and Federico Simmross-Wattenberg and Pablo Casaseca-de-la-Higuera and Marcos Mart{\'\i}n-Fern{\'a}ndez and Carlos Alberola-L{\'o}pez} } @article {947, title = {Magnetic Resonance Simulation in Education: Quantitative Evaluation of an Actual Classroom Experience}, journal = {Sensors}, volume = {21}, year = {2021}, pages = {6011}, abstract = {

Magnetic resonance is an imaging modality that implies a high complexity for radiographers. Despite some simulators having been developed for training purposes, we are not aware of any attempt to quantitatively measure their educational performance. The present study gives an answer to the question: Does an MRI simulator built on specific functional and non-functional requirements help radiographers learn MRI theoretical and practical concepts better than traditional educational method based on lectures? Our study was carried out in a single day by a total of 60 students of a main hospital in Madrid, Spain. The experiment followed a randomized pre-test post-test design with a control group that used a traditional educational method, and an experimental group that used our simulator. Knowledge level was assessed by means of an instrument with evidence of validity in its format and content, while its reliability was analyzed after the experiment. Statistical differences between both groups were measured. Significant statistical differences were found in favor of the participants who used the simulator for both the post-test score and the gain (difference between post-test and pre-test scores). The effect size turned out to be significant as well. In this work we evaluated a magnetic resonance simulation paradigm as a tool to help in the training of radiographers. The study shows that a simulator built on specific design requirements is a valuable complement to traditional education procedures, backed up with significant quantitative results.

}, author = {Trece{\~n}o-Fern{\'a}ndez, Daniel and Calabia-del-Campo, Juan and Matute-Teresa, F{\'a}tima and Bote-Lorenzo, Miguel L and G{\'o}mez-S{\'a}nchez, Eduardo and Rodrigo de Luis-Garc{\'\i}a and Alberola-L{\'o}pez, Carlos} } @article {943, title = {Medium-term changes in patients with epilepsy during the COVID-19 pandemic}, journal = {Acta Neurologica Scandinavica}, volume = {144}, year = {2021}, pages = {450-459}, abstract = {

Objectives: The novel coronavirus disease (COVID-19) pandemic has led to social distancing measures and impaired medical care of chronic neurological diseases, including epilepsy, which may have adversely affected well-being and quality of life of patients with epilepsy (PWE). The objective of this study is to evaluate the impact of the COVID-19 pandemic in the levels of anxiety, depression, somnolence, and quality of life using validated scales in PWE in real-life clinical practice.

Materials \& Methods: Self-administered scales of anxiety disorders (GAD-7), depression (NDDI-E), somnolence (Epworth Sleepiness Scale; ESS), and quality of life (QOLIE-31-P) in PWE treated in a Refractory Epilepsy Unit were longitudinally analyzed. Data were collected before the beginning (December 2019-March 2020) and during the COVID-19 pandemic (September 2020-January 2021).

Results: 158 patients (85 from the first round and 73 from the second round) 45.0 +- 17.3 years of age, 43.2\% women, epilepsy duration 23.0 +- 14.9 years, number of antiepileptic drugs 2.1 +- 1.4, completed the survey. Significant longitudinal reduction of QOLIE-31-P (from 58.9 +- 19.7 to 56.2 +- 16.2, p = 0.035) and GAD-7 scores (from 8.8 +- 6.2 to 8.3 +- 5.9, corrected p = .024) was identified. No statistically significant longitudinal changes in the number of seizures (from 0.9 +- 1.9 to 2.5 +- 6.2, p = .125) or NDDI-E scores (from 12.3 +- 4.3 to 13.4 +- 4.4, p = .065) were found. Significant longitudinal increase of ESS (from 4.9 +- 3.7 to 7.4 +- 4.9, p = .001) was found.

Conclusions: During the COVID-19 pandemic, quality of life and anxiety levels were lower in PWE, and sleepiness levels were raised, without seizure change.

}, keywords = {Anxiety, COVID-19, Sleep, epilepsy, pandemic, quality of life}, doi = {https://doi.org/10.1111/ane.13481}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/ane.13481}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and Vieira Campos, Alba and Mart{\'\i}nez-Dubarbie, Francisco and Vivancos, Jos{\'e} and De Toledo-Heras, Mar{\'\i}a} } @article {951, title = {Time-efficient three-dimensional transmural scar assessment provides relevant substrate characterization for ventricular tachycardia features and long-term recurrences in ischemic cardiomyopathy}, journal = {Scientific Reports}, volume = {11}, year = {2021}, month = {2021}, url = {https://www.nature.com/articles/s41598-021-97399-w}, author = {S. Merino-Caviedes and Guti{\'e}rrez, L. and Alfonso-Almaz{\'a}n, J. and Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and Quintanilla, J. and S{\'a}nchez-Gonz{\'a}lez, J. and Marina-Breysse, M. and Gal{\'a}n-Arriola, C. and Enr{\'\i}quez-V{\'a}zquez, D. and Torres, C. and Pizarro, G. and Ib{\'a}{\~n}ez, B. and Peinado, R. and Merino, J. and P{\'e}rez-Villacast{\'\i}n, J. and Jalife. J and L{\'o}pez-Yunta, M. and V{\'a}zquez, M. and Aguado-Sierra, J. and Gonz{\'a}lez-Ferrer, J. and P{\'e}rez-Castellano, N. and Mart{\'\i}n-Fern{\'a}ndez, M. and Alberola-L{\'o}pez, C and Filgueiras-Rama, D.} } @article {933, title = {On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge}, journal = {NeuroImage}, year = {2021}, month = {2021}, pages = {118367}, issn = {1053-8119}, doi = {https://doi.org/10.1016/j.neuroimage.2021.118367}, url = {https://www.sciencedirect.com/science/article/pii/S1053811921006431}, author = {Alberto De Luca and Andrada Ianus and Alexander Leemans and Marco Palombo and Noam Shemesh and Hui Zhang and Daniel C. Alexander and Markus Nilsson and Martijn Froeling and Geert-Jan Biessels and Mauro Zucchelli and Matteo Frigo and Enes Albay and Sara Sedlar and Abib Alimi and Samuel Deslauriers-Gauthier and Rachid Deriche and Rutger Fick and Maryam Afzali and Tomasz Pieciak and Fabian Bogusz and Santiago Aja-Fern{\'a}ndez and Evren {\"O}zarslan and Derek K. Jones and Haoze Chen and Mingwu Jin and Zhijie Zhang and Fengxiang Wang and Vishwesh Nath and Prasanna Parvathaneni and Jan Morez and Jan Sijbers and Ben Jeurissen and Shreyas Fadnavis and Stefan Endres and Ariel Rokem and Eleftherios Garyfallidis and Irina Sanchez and Vesna Prchkovska and Paulo Rodrigues and Bennet A. Landman and Kurt G. Schilling} } @article {912, title = {On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge}, journal = {bioRxiv}, year = {2021}, month = {2021}, doi = {10.1101/2021.03.02.433228}, url = {https://www.biorxiv.org/content/early/2021/03/02/2021.03.02.433228}, author = {De Luca, Alberto and Ianus, Andrada and Leemans, Alexander and Palombo, Marco and Shemesh, Noam and Zhang, Hui and Alexander, Daniel C and Nilsson, Markus and Froeling, Martijn and Biessels, Geert-Jan and Zucchelli, Mauro and Frigo, Matteo and Albay, Enes and Sedlar, Sara and Alimi, Abib and Deslauriers-Gauthier, Samuel and Deriche, Rachid and Fick, Rutger and Maryam Afzali and Tomasz Pieciak and Bogusz, Fabian and Santiago Aja-Fern{\'a}ndez and Ozarslan, Evren and Derek K. Jones and Chen, Haoze and Jin, Mingwu and Zhang, Zhijie and Wang, Fengxiang and Nath, Vishwesh and Parvathaneni, Prasanna and Morez, Jan and Sijbers, Jan and Jeurissen, Ben and Fadnavis, Shreyas and Endres, Stefan and Rokem, Ariel and Garyfallidis, Eleftherios and Sanchez, Irina and Prchkovska, Vesna and Rodrigues, Paulo and Landman, Bennet A and Schilling, Kurt G} } @conference {917, title = {The utility of the GAD-7 anxiety, NDDI-E depression, Epworth sleepiness and QOLIE-31-P quality of life scales in patients with epilepsy in real clinical practice (2379)}, booktitle = {Proceedings of the American Academy of Neurology 2021 Virtual Annual Meeting}, year = {2021}, publisher = {Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology}, organization = {Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology}, abstract = {

Objective: The objective of this project is to study the presence of psychiatric comorbidity (anxiety and depression), somnolence and quality of life using validated scales in patients with epilepsy in real clinical practice, and its relationship with other clinical and demographic variables.

Background: Previous studies have shown that psychiatric comorbidity, specially anxiety and depression, as well as sleep disorders are more prevalent in patients with epilepsy than in the general population.

Design/Methods: Cross-sectional descriptive observational study using validated scales of anxiety disorders(GAD-7), depression(NDDI-E), sleep disorders(Epworth) and quality of life(QOLIE-31-P) in patients with epilepsy treated in the Refractory Epilepsy Unit of a tertiary hospital.

Results: We recruited 84 patients, age 44.3 {\textpm} 17.4 years, 48.2\% women, duration of epilepsy 21.5 {\textpm} 15.9 years, number of antiepileptic drugs 1.9 {\textpm} 1.2. We found severe anxiety(GAD-7\> 14) in 14.3\%, depression(NDDI-E\> 15) in 20.2\%; abnormal sleepiness(Epworth\> 10) in 14.3\% of patients, and QOLIE-31-P 62.0 {\textpm} 19.2. Each more point in GAD-7 is 21\% more likely to suffer from anxiety(OR 1.21; 95\% CI 1.09{\textendash}1.36; p = 0.0008), NDDI-E scores\<=15 represent 85 \% less chance of having depression(OR 0.15; 95\% CI 0.04{\textendash}0.51]; p = 0.002). We found a positive association between depression according to NDDI-E with seizure frequency(p = 0.017) and number of drugs(p = 0.019); and severe anxiety according to GAD-7 and number of drugs(p = 0.019). We found a negative correlation between QOLIE-31-P with NDDI-E(r = -0.68; p \<0.0001) and GAD-7(r = -0.76; p \<0.0001).

Conclusions: Validated scales in epilepsy for the detection of anxiety(GAD-7) and depression(NDDI-E) are useful in the detection of these disorders in real clinical practice. The assessment of the presence of anxiety-depressive psychiatric comorbidity is especially relevant in patients with a higher frequency of seizures, a greater number of drugs and a poorer quality of life.

}, url = {https://n.neurology.org/content/96/15_Supplement/2379}, author = {Gonzalez-Martinez, Alicia and {\'A}lvaro Planchuelo-G{\'o}mez and Mart{\'\i}nez-Dubarbie, Francisco and Vieira Campos, Alba and Vivancos, Jos{\'e} and De Toledo, Mar{\'\i}a} } @article {zhao2020doa, title = {DoA Prediction Based Beamforming with Low Training Overhead for Highly-Mobile UAV Communication with Cellular Networks}, journal = {Applied Sciences}, volume = {10}, number = {13}, year = {2020}, pages = {4420}, publisher = {Multidisciplinary Digital Publishing Institute}, author = {Zhao, Tianxiao and Luo, Chunbo and Zhou, Jianming and Guo, Dechun and Chen, Ning and Pablo Casaseca-de-la-Higuera} } @article {887, title = {Factors associated with the presence of headache in hospitalized COVID-19 patients and impact on prognosis: a retrospective cohort study}, journal = {The Journal of Headache and Pain}, volume = {21}, year = {2020}, month = {Jul}, pages = {94}, abstract = {Headache is one of the most frequent neurologic manifestations in COVID-19. We aimed to analyze which symptoms and laboratory abnormalities were associated with the presence of headache and to evaluate if patients with headache had a higher adjusted in-hospital risk of mortality.}, issn = {1129-2377}, doi = {10.1186/s10194-020-01165-8}, url = {https://doi.org/10.1186/s10194-020-01165-8}, author = {Trigo, Javier and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}lvaro Planchuelo-G{\'o}mez and Mart{\'\i}nez-P{\'\i}as, Enrique and Talavera, Blanca and Hern{\'a}ndez-P{\'e}rez, Isabel and Valle-Pe{\~n}acoba, Gonzalo and Sim{\'o}n-Campo, Paula and de Lera, Mercedes and Chavarr{\'\i}a-Miranda, Alba and L{\'o}pez-Sanz, Cristina and Guti{\'e}rrez-S{\'a}nchez, Mar{\'\i}a and Mart{\'\i}nez-Velasco, Elena and Pedraza, Mar{\'\i}a and Sierra, {\'A}lvaro and G{\'o}mez-Vicente, Beatriz and Juan F Arenillas and {\'A}ngel L. Guerrero} } @article {853, title = {Groupwise Non-Rigid Registration with Deep Learning: An Affordable Solution Applied to 2D Cardiac Cine MRI Reconstruction}, journal = {Entropy}, volume = {22}, year = {2020}, pages = {687}, doi = {https://doi.org/10.3390/e22060687}, url = {https://www.mdpi.com/1099-4300/22/6/687}, author = {Mart{\'\i}n-Gonz{\'a}lez, Elena and Sevilla, Teresa and Revilla-Orodea, Ana and Pablo Casaseca-de-la-Higuera and Alberola-L{\'o}pez, Carlos} } @article {854, title = {Integration of an Intelligent Tutoring System in a Magnetic Resonance Simulator for Education: Technical Feasibility and User Experience}, journal = {Computer Methods and Programs in Biomedicine}, year = {2020}, pages = {105634}, doi = {https://doi.org/10.1016/j.cmpb.2020.105634}, url = {https://authors.elsevier.com/a/1bM7z_3sJeWiZh}, author = {Trece{\~n}o-Fern{\'a}ndez, Daniel and Calabia-del-Campo, Juan and Bote-Lorenzo, Miguel L and G{\'o}mez-S{\'a}nchez, Eduardo and Rodrigo de Luis-Garc{\'\i}a and Alberola-L{\'o}pez, Carlos} } @article {842, title = {Objective ADHD diagnosis using Convolutional Neural Networks over Daily-Life Activity Records}, journal = {IEEE Journal of Biomedical and Health Informatics}, year = {2020}, author = {Amado-Caballero, Patricia and Pablo Casaseca-de-la-Higuera and Alberola-Lopez, Susana and Jesus Maria Andres-de-Llano and Lopez-Villalobos, Jose Antonio and Garmendia-Leiza, Jose Ramon and Carlos Alberola-Lopez} } @article {913, title = {Simultaneous imaging of hard and soft biological tissues in a low-field dental MRI scanner}, journal = {Scientific Reports}, volume = {10}, year = {2020}, month = {2021}, pages = {1{\textendash}14}, author = {Algarin, Jose M and Diaz-Caballero, Elena and Borreguero, Jose and Galve, Fernando and Grau-Ruiz, Daniel and Rigla, Juan P and Bosch, Ruben and Gonzalez, Jose M and Pallas, Eduardo and Corberan, Miguel and Carlos Gramage and Santiago Aja-Fern{\'a}ndez and Alfonso R{\'\i}os and Jos{\'e} M. Benlloch and Joseba Alonso} } @article {897, title = {Simultaneous imaging of hard and soft biological tissues in a low-field dental MRI scanner}, journal = {Scientific Reports volume }, volume = {10}, year = {2020}, month = {2020}, chapter = {21470}, doi = {https://doi.org/10.1038/s41598-020-78456-2}, url = {https://www.nature.com/articles/s41598-020-78456-2}, author = {Jos{\'e} M. Algar{\'\i}n and Elena D{\'\i}az-Caballero and Jos{\'e} Borreguero and Fernando Galve and Daniel Grau-Ruiz and Juan P. Rigla and Rub{\'e}n Bosch and Jos{\'e} M. Gonz{\'a}lez and Eduardo Pall{\'a}s and Miguel Corber{\'a}n and Carlos Gramage and Santiago Aja-Fern{\'a}ndez and Santiago Aja-Fern{\'a}ndez and Jos{\'e} M. Benlloc and Joseba Alonso} } @article {martinez2020smartphone, title = {Smartphone-based object recognition with embedded machine learning intelligence for unmanned aerial vehicles}, journal = {Journal of Field Robotics}, volume = {37}, number = {3}, year = {2020}, pages = {404{\textendash}420}, author = {Martinez-Alpiste, Ignacio and Pablo Casaseca-de-la-Higuera and Jose-Maria Alcaraz-Calero and Grecos, Christos and Wang, Qi} } @article {san2020two, title = {Two-stage memetic algorithm for blind equalisation in direct-sequence/code-division multiple-access systems}, journal = {IET Communications}, year = {2020}, publisher = {IET Digital Library}, author = {San-Jos{\'e}-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @article {841, title = {A Web-Based Educational Magnetic Resonance Simulator: Design, Implementation and Testing}, journal = {Journal of Medical Systems}, volume = {44}, year = {2020}, month = {2020}, pages = {9}, author = {Trece{\~n}o-Fern{\'a}ndez, Daniel and Calabia-del-Campo, Juan and Bote-Lorenzo, Miguel L and S{\'a}nchez, Eduardo G{\'o}mez and Rodrigo de Luis-Garc{\'\i}a and Alberola-L{\'o}pez, Carlos} } @article {san2020new, title = {A new flower pollination algorithm for equalization in synchronous DS/CDMA multiuser communication systems}, journal = {Soft Computing}, year = {2020}, month = {2000}, pages = {1{\textendash}15}, publisher = {Springer Berlin Heidelberg}, author = {San-Jos{\'e}-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @article {805, title = {Air Infiltration Monitoring using Thermography and Neural Networks}, journal = {Energy and Buildings}, volume = {191}, year = {2019}, month = {05/2019}, pages = {187-199}, chapter = {187}, author = {A Royuela and M A Padilla-Marcos and A Meiss and Pablo Casaseca-de-la-Higuera and J Feij{\'o}-Mu{\~n}oz} } @conference {martinez2019benchmarking, title = {Benchmarking Machine-Learning-Based Object Detection on a UAV and Mobile Platform}, booktitle = {2019 IEEE Wireless Communications and Networking Conference (WCNC)}, year = {2019}, pages = {1{\textendash}6}, publisher = {IEEE}, organization = {IEEE}, author = {Martinez-Alpiste, Ignacio and Pablo Casaseca-de-la-Higuera and Jose-Maria Alcaraz-Calero and Grecos, Christos and Wang, Qi} } @article {802, title = {Efficient QoE-Aware Scheme for Video Quality Switching Operations in Dynamic Adaptive Streaming}, journal = {ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)}, volume = {15}, year = {2019}, pages = {17}, author = {Irondi, Iheanyi and Wang, Qi and Grecos, Christos and Calero, Jose M Alcaraz and Pablo Casaseca-de-la-Higuera} } @conference {hoyos2019evaluation, title = {Evaluation in a real environment of a trainable cough monitoring app for smartphones}, booktitle = {Mediterranean Conference on Medical and Biological Engineering and Computing}, year = {2019}, pages = {1175{\textendash}1180}, publisher = {Springer, Cham}, organization = {Springer, Cham}, author = {Hoyos-Barcel{\'o}, Carlos and Garmendia-Leiza, Jos{\'e} Ram{\'o}n and MD Aguilar-Garcia and Monge-{\'A}lvarez, Jes{\'u}s and P{\'e}rez-Alonso, Diego Asay and Alberola-L{\'o}pez, Carlos and Pablo Casaseca-de-la-Higuera} } @article {801, title = {A Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {66}, year = {2019}, pages = {2319-2330}, author = {Monge-Alvarez, Jesus and Hoyos-Barcelo, Carlos and San Jose-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @conference {jimenez2019novel, title = {A Novel Design Method for Digital FIR/IIR Filters Based on the Shuffle Frog-Leaping Algorithm}, booktitle = {2019 27th European Signal Processing Conference (EUSIPCO)}, year = {2019}, pages = {1{\textendash}5}, publisher = {IEEE}, organization = {IEEE}, author = {Jim{\'e}nez-Galindo, Daniel and Pablo Casaseca-de-la-Higuera and San-Jos{\'e}-Revuelta, Luis M} } @article {menchon2019reconstruction, title = {Reconstruction techniques for cardiac cine MRI}, journal = {Insights into imaging}, volume = {10}, number = {1}, year = {2019}, pages = {100}, publisher = {Springer Berlin Heidelberg}, author = {Mench{\'o}n-Lara, Rosa-Mar{\'\i}a and Simmross-Wattenberg, Federico and Pablo Casaseca-de-la-Higuera and Mart{\'\i}n-Fern{\'a}ndez, Marcos and Alberola-L{\'o}pez, Carlos} } @article {803, title = {Robust detection of audio-cough events using local Hu moments}, journal = {IEEE journal of biomedical and health informatics}, volume = {23}, year = {2019}, pages = {184{\textendash}196}, author = {Monge-{\'A}lvarez, Jes{\'u}s and Hoyos-Barcel{\'o}, Carlos and Lesso, Paul and Pablo Casaseca-de-la-Higuera} } @article {796, title = {A Second Order Multi-Stencil Fast Marching Method With a Non-Constant Local Cost Model}, journal = {IEEE Transactions on Image Processing}, volume = {28}, year = {2019}, month = {04/2019}, pages = {1967{\textendash}1979}, abstract = {

The fast marching method is widely employed in several fields of image processing. Some years ago a multi-stencil version (MSFM) was introduced to improve its accuracy by solving the equation for a set of stencils and choosing the best solution at each considered node. The following work proposes a modified numerical scheme for MSFM to take into account the variation of the local cost, which has proven to be second order. The influence of the stencil set choice on the algorithm outcome with respect to stencil orthogonality and axis swapping is also explored, where stencils are taken from neighborhoods of varying radius. The experimental results show that the proposed schemes improve the accuracy of their original counterparts, and that the use of permutation-invariant stencil sets provides robustness against shifted vector coordinates in the stencil set.

}, keywords = {Approximation algorithms, Differential equations, Eikonal equation, Frequency modulation, MSFM, Mathematical model, Silicon, Three-dimensional displays, Unmanned aerial vehicles, Vectors, axis swapping, difference equations, fast marching methods, finite difference methods, finite differences, image processing, iterative methods, least squares approximations, multi-stencil schemes, multistencil version, nonconstant local cost model, permutation-invariant stencil sets, second order multistencil fast marching method, stencil orthogonality, stencil set}, issn = {1057-7149}, doi = {10.1109/TIP.2018.2880507}, url = {https://ieeexplore.ieee.org/document/8531783/}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and M. T. P{\'e}rez and Pablo Casaseca-de-la-Higuera and M. Mart{\'\i}n-Fern{\'a}ndez and R. Deriche and C. Alberola-L{\'o}pez} } @article {769, title = {Audio-cough event detection based on moment theory}, journal = {Applied Acoustics}, volume = {135}, year = {2018}, pages = {124{\textendash}135}, author = {Monge-{\'A}lvarez, Jes{\'u}s and Hoyos-Barcel{\'o}, Carlos and Dahal, Keshav and Pablo Casaseca-de-la-Higuera} } @article {772, title = {Characterisation of Received Signal Strength Perturbations using Allan Variance}, journal = {IEEE Transactions on Aerospace and Electronic Systems}, volume = {54}, year = {2018}, pages = {873-889}, chapter = {873}, author = {Luo, Chunbo and Pablo Casaseca-de-la-Higuera and McClean, Sally and Parr, Gerard and Ren, Peng} } @conference {800, title = {Compressed UAV sensing for flood monitoring by solving the continuous travelling salesman problem over hyperspectral maps}, booktitle = {Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2018}, year = {2018}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Pablo Casaseca-de-la-Higuera and Antonio Trist{\'a}n-Vega and Hoyos-Barcel{\'o}, Carlos and S. Merino-Caviedes and Wang, Qi and Luo, Chunbo and Wang, Xinheng and Wang, Zhi} } @article {799, title = {Efficient computation of image moments for robust cough detection using smartphones}, journal = {Computers in biology and medicine}, volume = {100}, year = {2018}, pages = {176{\textendash}185}, author = {Hoyos-Barcel{\'o}, Carlos and Monge-{\'A}lvarez, Jes{\'u}s and Pervez, Zeeshan and San-Jos{\'e}-Revuelta, Luis M and Pablo Casaseca-de-la-Higuera} } @article {771, title = {Efficient k-NN Implementation for Real-Time Detection of Cough Events in Smartphones}, journal = {IEEE Journal of Biomedical and Health Informatics}, volume = {23}, year = {2018}, pages = {1662-1671}, chapter = {1662}, author = {Hoyos-Barcel{\'o}, Carlos and Monge-{\'A}lvarez, Jes{\'u}s and Shakir, Muhammad Zeeshan and Jose-Maria Alcaraz-Calero and Pablo Casaseca-de-la-Higuera} } @conference {784, title = {Joint Image Reconstruction and Phase Corruption Maps Estimation in Multi-Shot Echo Planar Imaging}, booktitle = {MICCAI}, year = {2018}, month = {09/2018}, publisher = {MICCAI}, organization = {MICCAI}, address = {Granada}, abstract = {

Multishot echo-planar imaging is a common strategy in diffusion Magnetic Resonance Imaging to reduce the artifacts caused by the long echo-trains in single-shot acquisitions. However, it su ers from shot-to-shot phase discrepancies associated to subject motion, which can notably degrade the quality of the reconstructed image. Consequently, some
type of motion-induced phases error correction needs to be incorporated into the reconstruction process. In this paper we focus on ridig motion induced errors, which have proved to corrupt the shots with linear phase maps. By incorporating this prior knowledge, we propose a maximum likelihood formulation that estimates both the parameters that characterize the linear phase maps and the reconstructed image. In order to make the problem tractable, we follow a greedy iterative procedure that alternates between the estimation of each of them. Simulation data are used to illustrate the performance of the method against state-of-the-art alternatives.

}, author = {I{\~n}aki Rabanillo-Viloria and Santiago Sanz-Est{\'e}banez and Santiago Aja-Fern{\'a}ndez and Joseph V. Hajnal and Carlos Alberola-L{\'o}pez and Lucilio Cordero-Grande} } @conference {804, title = {Mapping Raw Acceleration Data on ActiGraph Counts: A Machine Learning Approach}, booktitle = {Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality}, year = {2018}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {ActiGraph, Actimetry, Microsoft Band 2, counts}, isbn = {978-1-4503-6518-5}, doi = {10.1145/3284179.3284260}, url = {http://doi.acm.org/10.1145/3284179.3284260}, author = {Mart{\'\i}n-Gonz{\'a}lez, Elena and Rodrigo de Luis-Garc{\'\i}a and Pablo Casaseca-de-la-Higuera and Garmendia-Leiza, J. R. and Jesus Maria Andres-de-Llano and Alberola-L{\'o}pez, Carlos} } @conference {785, title = {Robust Windowed Harmonic Phase Analysis with a Single Acquisition}, booktitle = {MICCAI }, year = {2018}, month = {2018}, publisher = {MICCAI}, organization = {MICCAI}, address = {Granada}, abstract = {

The HARP methodology is a widely extended procedure for cardiac tagged magnetic resonance imaging since it is able to analyse local mechanical behaviour of the heart; extensions and improvements of this method have also been reported since HARP was released. Acquisition of an over-determined set of orientations is one of such alternatives,
which has notably increased HARP robustness at the price of increasing examination time. In this paper, we explore an alternative to this method based on the use of multiple peaks, as opposed to multiple orientations, intended for a single acquisition. Performance loss is explored with respect to multiple orientations in a real setting. In addition, we have assessed, by means of a computational phantom, optimal tag orientations and spacings of the stripe pattern by minimizing the Frobenius norm of the difference between the ground truth and the estimated material deformation gradient tensor. Results indicate that, for a single acquisition, multiple peaks as opposed to multiple orientations, are indeed preferable.

}, keywords = {Cardiac Tagged Magnetic Resonance Imaging, HARmonic Phase, Multi-Harmonic Analysis, Robust Strain Reconstruction}, author = {Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and Marcos Martin-Fern{\'a}ndez and Carlos Alberola L{\'o}pez} } @inbook {757, title = {Techniques for tracking: image registration}, booktitle = {Handbook of Speckle Filtering and Tracking in Cardiovascular Ultrasound Imaging and Video}, year = {2018}, publisher = {IET}, organization = {IET}, chapter = {15}, issn = {978-1-78561-290-9}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @conference {mi2018towards, title = {Towards Optimal Power Splitting in Simultaneous Power and Information Transmission}, booktitle = {2018 IEEE Global Communications Conference (GLOBECOM)}, year = {2018}, pages = {1{\textendash}6}, publisher = {IEEE}, organization = {IEEE}, author = {Mi, Yang and Luo, Chunbo and Min, Geyong and Pablo Casaseca-de-la-Higuera and Wang, Zhi} } @article {749, title = {Vortical Features for Myocardial Rotation Assessment in Hypertrophic Cardiomyopathy using Cardiac Tagged Magnetic Resonance}, journal = {Medical Image Analysis}, volume = {In Press}, year = {2018}, month = {04/2018}, type = {Original Article}, abstract = {

Left ventricular rotational motion is a feature of normal and diseased cardiac function. However, classical torsion and twist measures rely on the definition of a rotational axis which may not exist. This paper reviews global and local rotation descriptors of myocardial motion and introduces new curl-based (vortical) features built from tensorial magnitudes, intended to provide better comprehension about fibrotic tissue characteristics mechanical properties. Fifty-six cardiomyopathy patients and twenty-two healthy volunteers have been studied using tagged magnetic resonance by means of harmonic phase analysis. Rotation descriptors are built, with no assumption about a regular geometrical model, from different approaches. The extracted vortical features have been tested by means of a sequential cardiomyopathy classification procedure; they have proven useful for the regional characterization of the left ventricular function by showing great separability not only between pathologic and healthy patients but also, and specifically, between heterogeneous phenotypes within cardiomyopathies.

}, doi = {10.1016/j.media.2018.03.005}, author = {Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and T. Sevilla-Ruiz and A. Revilla-Orodea and Rodrigo de Luis-Garc{\'\i}a and M Martin-Fernandez and Carlos Alberola-Lopez} } @article {768, title = {A novel infrared video surveillance system using deep learning based techniques}, journal = {Multimedia Tools and Applications}, volume = {77}, year = {2018}, chapter = {26657}, author = {Zhang, Huaizhong and Luo, Chunbo and Wang, Qi and Kitchin, Matthew and Parmley, Andrew and Monge-Alvarez, Jesus and Pablo Casaseca-de-la-Higuera} } @article {698, title = {Abnormal Capillary Vasodynamics Contribute to Ictal Neurodegeneration in Epilepsy}, journal = {Scientific Reports}, volume = {7}, year = {2017}, abstract = {

Seizure-driven brain damage in epilepsy accumulates over time, especially in the hippocampus, which can lead to sclerosis, cognitive decline, and death. Excitotoxicity is the prevalent model to explain ictal neurodegeneration. Current labeling technologies cannot distinguish between excitotoxicity and hypoxia, however, because they share common molecular mechanisms. This leaves open the possibility that undetected ischemic hypoxia, due to ictal blood flow restriction, could contribute to neurodegeneration previously ascribed to excitotoxicity. We tested this possibility with Confocal Laser Endomicroscopy (CLE) and novel stereological analyses in several models of epileptic mice. We found a higher number and magnitude of NG2+ mural-cell mediated capillary constrictions in the hippocampus of epileptic mice than in that of normal mice, in addition to spatial coupling between capillary constrictions and oxidative stressed neurons and neurodegeneration. These results reveal a role for hypoxia driven by capillary blood flow restriction in ictal neurodegeneration. {\textcopyright} 2017 The Author(s).

}, doi = {10.1038/srep43276}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014072909\&doi=10.1038\%2fsrep43276\&partnerID=40\&md5=e9d3567266bdc360a7addc92be350c8d}, author = {Leal-Campanario, R. and Alarcon-Martinez, L. and Rieiro, H. and Martinez-Conde, S. and Alarcon-Martinez, T. and Zhao, X. and LaMee, J. and Popp, P.J. and Calhoun, M.E. and J I Arribas and Schlegel, A.A. and Di Stasi, L.L. and Rho, J.M. and Inge, L. and Otero-Millan, J. and Treiman, D.M. and Macknik, S.L.} } @article {773, title = {Matching pursuit-based compressive sensing in a wearable biomedical accelerometer fall diagnosis device}, journal = {Biomedical signal processing and control}, volume = {33}, year = {2017}, pages = {96{\textendash}108}, author = {Gibson, Ryan M and Amira, Abbes and Ramzan, Naeem and Pablo Casaseca-de-la-Higuera and Pervez, Zeeshan} } @conference {775, title = {Effect of importance sampling on robust segmentation of audio-cough events in noisy environments}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the}, year = {2016}, publisher = {IEEE}, organization = {IEEE}, author = {Monge-Alvarez, Jes{\'u}s and Hoyos-Barcel{\'o}, Carlos and Lesso, Paul and Escudero, Javier and Dahal, Keshav and Pablo Casaseca-de-la-Higuera} } @article {616, title = {Influence of ultrasound speckle tracking strategies for motion and strain estimation}, journal = {Medical Image Analysis}, volume = {32}, year = {2016}, month = {2016}, pages = {184 - 200}, abstract = {

Abstract Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system.

}, issn = {1361-8415}, doi = {http://dx.doi.org/10.1016/j.media.2016.04.002}, url = {http://www.sciencedirect.com/science/article/pii/S1361841516300202}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @article {602, title = {Jacobian weighted temporal total variation for motion compensated compressed sensing reconstruction of dynamic MRI}, journal = {Magnetic Resonance in Medicine}, year = {2016}, month = {2016}, abstract = {

Purpose:\ To eliminate the need of spatial intraframe regularization in a recently reported dynamic MRI compressed-sensing-based reconstruction method with motion compensation and to increase its performance.

Theory and Methods: We propose a new regularization metric based on the introduction of a spatial weighting measure given by the Jacobian of the estimated deformations. It shows convenient discretization properties and, as a byproduct, it also provides a theoretical support to a result reported by others based on an intuitive design. The method has been applied to the reconstruction of both short and long axis views of the heart of four healthy volunteers. Quantitative image quality metrics as well as straightforward visual assessment are reported.

Results: Short and long axis reconstructions of cardiac cine MRI sequences have shown superior results than previously reported methods both in terms of quantitative metrics and of visual assessment. Fine details are better preserved due to the lack of additional intraframe regularization, with no significant image artifacts even for an acceleration factor of 12.

Conclusions: The proposed Jacobian Weighted temporal Total Variation results in better reconstructions of highly undersampled cardiac cine MRI than previously proposed methods and sets a theoretical ground for forward and backward predictors used elsewhere.

}, keywords = {compressed sensing, dynamic MRI reconstruction, group-wise registration, motion estimation}, doi = {10.1002/mrm.26198}, url = {http://onlinelibrary.wiley.com/doi/10.1002/mrm.26198}, author = {J Royuela-del-Val and Lucilio Cordero-Grande and Federico Simmross-Wattenberg and Mart{\'\i}n-Fern{\'a}ndez, M and Carlos Alberola-Lopez} } @article {597, title = {Multi-oriented windowed harmonic phase reconstruction for robust cardiac strain imaging}, journal = {Medical Image Analysis}, volume = {29}, year = {2016}, month = {2016}, pages = {1-11}, chapter = {1}, author = {Lucilio Cordero-Grande and J Royuela-del-Val and Santiago Sanz-Est{\'e}banez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {776, title = {Multiple comparator classifier framework for accelerometer-based fall detection and diagnostic}, journal = {Applied Soft Computing}, volume = {39}, year = {2016}, pages = {94{\textendash}103}, author = {Gibson, Ryan M and Amira, Abbes and Ramzan, Naeem and Pablo Casaseca-de-la-Higuera and Pervez, Zeeshan} } @conference {603, title = {Multiresolution Reconstruction of Real-Time MRI with Motion Compensated Compressed Sensing: Application to 2D Free-Breathing Cardiac MRI}, booktitle = {International Symposium on Biomedical Engineering: From Nano to Macro}, year = {2016}, month = {2016}, publisher = {IEEE Signal Processing Society}, organization = {IEEE Signal Processing Society}, address = {Prague, Check Republic}, abstract = {

Real-time MRI is a novel noninvasive imaging technique that allows the visualization of physiological processes with both good spatial and temporal resolutions. However, the reconstruction of images from highly undersampled data, needed to perform real-time imaging, remains challenging. Recently, the combination of Compressed Sensing theory with motion compensation techniques has shown to achieve better results than previous methods. In this work we describe a real-time MRI algorithm based on the acquisition of the k-space data following a Golden Radial trajectory, Compressed Sensing reconstruction and a groupwise temporal registration algorithm for the estimation and compensation of the motion in the image, all this embedded within a temporal multiresolution scheme. We have applied the proposed method to the reconstruction of free-breathing acquisition of short axis views of the heart, achieving a temporal resolution of 25ms, corresponding to an acceleration factor of 28 with respect to fully sampled Cartesian acquisitions.

}, keywords = {Compressive sensing \& sampling, Image reconstruction {\textendash} analytical \& iterative methods, Magnetic resonance imaging (MRI)}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and M. Mart{\'\i}n-Fern{\'a}ndez and Federico Simmross-Wattenberg and Claudia Prieto and Carlos Alberola-Lopez} } @conference {615, title = {Spatial and Spectral Anisotropy in HARP Images: An Automated Approach}, booktitle = {International Symposium on Biomedical Imaging: From Nano to Macro (ISBI2016)}, year = {2016}, month = {2016}, address = {Prague, Czech Republic}, abstract = {

Strain and related tensors play a major role in cardiac function\ characterization, so correct estimation of the local phase\ in tagged images is crucial for quantitative myocardial motion\ studies. We propose an Harmonic Phase related procedure\ that is adaptive in the spatial and the spectral domains: as for\ the former, we use an angled-steered analysis window prior to\ the Fourier Transform; as for the latter, the bandpass filter is\ also angle-adaptive. Both of them are narrow in the modulation\ direction and wide in the orthogonal direction.

Moreover,\ no parameters are manually set since their values are partially\ based on the information available at the DICOM headers and\ additional information is estimated from data. The procedure
is tested in terms of accuracy (on synthetic data) and reproducibility\ (on real data) of the deformation gradient tensor,\ measured by means of the distribution of the Frobenius norm\ differences between two tensor datasets.

}, keywords = {Anisotropic Gaussian Window, Automatic Band-Pass Filtering, HARmonic Phase, Strain Tensor, Tagged Magnetic Resonance Imaging, Thresholding}, author = {Santiago Sanz-Est{\'e}banez and Lucilio Cordero-Grande and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {774, title = {Systematic infrared image quality improvement using deep learning based techniques}, booktitle = {Remote Sensing Technologies and Applications in Urban Environments}, year = {2016}, publisher = {International Society for Optics and Photonics}, organization = {International Society for Optics and Photonics}, author = {Zhang, Huaizhong and Pablo Casaseca-de-la-Higuera and Luo, Chunbo and Wang, Qi and Kitchin, Matthew and Parmley, Andrew and Monge-Alvarez, Jesus} } @conference {690, title = {Whole-heart single breath-hold cardiac cine: A robust motion-compensated compressed sensing reconstruction method}, booktitle = {International Workshop on Reconstruction and Analysis of Moving Body Organs (RAMBO/MICCAI) }, year = {2016}, month = {2016}, address = {Athens, Greece}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and Marcos Mart{\'\i}n-Fern{\'a}ndez and Federico Simmross-Wattenberg and Claudia Prieto and Carlos Alberola-Lopez} } @article {de2014attention, title = {Attention Deficit/Hyperactivity Disorder and Medication with Stimulants in Young Children: A DTI Study}, journal = {Progress in Neuro-Psychopharmacology and Biological Psychiatry}, volume = {57}, year = {2015}, publisher = {Elsevier}, chapter = {176}, doi = {http://dx.doi.org/10.1016/j.pnpbp.2014.10.014}, author = {Rodrigo de Luis-Garc{\'\i}a and Cab{\'u}s-Pi{\~n}ol, Gemma and Imaz-Roncero, Carlos and Daniel Argibay-Qui{\~n}ones and Gonzalo Barrio-Arranz and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @proceedings {574, title = {Effect of Downsampling and Compressive Sensing on Audio-based Continuous Cough Monitoring}, volume = {37}, year = {2015}, pages = {6231-6235}, address = {Milan, Italy}, author = {Pablo Casaseca-de-la-Higuera and Lesso, Paul and Mckinstry, Brian and Pinnock, Hilary and Rabinovich, Roberto and McCloughan, Lucy and Monge-{\'A}lvarez, Jes{\'u}s} } @article {431, title = {Fast calculation of alpha-stable density functions based on off-line precomputations. Application to ML parameter estimation}, journal = {Digital Signal Processing}, volume = {38}, year = {2015}, pages = {1-12}, chapter = {1}, keywords = {Delaunay triangulation, Interpolation, Parameter estimation, alpha-Stable}, doi = {10.1016/j.dsp.2014.12.009}, author = {Federico Simmross-Wattenberg and Marcos Mart{\'\i}n-Fern{\'a}ndez and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @article {541, title = {A Maximum Likelihood Approach to Diffeomorphic Speckle Tracking for 3D Strain Estimation in Echocardiography}, journal = {Medical Image Analysis}, year = {2015}, pages = {-}, abstract = {

Abstract The strain and strain-rate measures are commonly used for the analysis and assessment of regional myocardial function. In echocardiography (EC), the strain analysis became possible using Tissue Doppler Imaging (TDI). Unfortunately, this modality shows an important limitation: the angle between the myocardial movement and the ultrasound beam should be small to provide reliable measures. This constraint makes it difficult to provide strain measures of the entire myocardium. Alternative non-Doppler techniques such as Speckle Tracking (ST) can provide strain measures without angle constraints. However, the spatial resolution and noisy appearance of speckle still make the strain estimation a challenging task in EC. Several maximum likelihood approaches have been proposed to statistically characterize the behavior of speckle, which results in a better performance of speckle tracking. However, those models do not consider common transformations to achieve the final B-mode image (e.g. interpolation). This paper proposes a new maximum likelihood approach for speckle tracking which effectively characterizes speckle of the final B-mode image. Its formulation provides a diffeomorphic scheme than can be efficiently optimized with a second-order method. The novelty of the method is threefold: First, the statistical characterization of speckle generalizes conventional speckle models (Rayleigh, Nakagami and Gamma) to a more versatile model for real data. Second, the formulation includes local correlation to increase the efficiency of frame-to-frame speckle tracking. Third, a probabilistic myocardial tissue characterization is used to automatically identify more reliable myocardial motions. The accuracy and agreement assessment was evaluated in a set of 16 synthetic image sequences for three different scenarios: normal, acute ischemia and acute dyssynchrony. The proposed method was compared to six speckle tracking methods. Results revealed that the proposed method is the most accurate method to measure the motion and strain with an average median motion error of 0.42\ mm and a median strain error of 2.0 {\textpm} 0.9\%, 2.1 {\textpm} 1.3\% and 7.1 {\textpm} 4.9\% for circumferential, longitudinal and radial strain respectively. It also showed its capability to identify abnormal segments with reduced cardiac function and timing differences for the dyssynchrony cases. These results indicate that the proposed diffeomorphic speckle tracking method provides robust and accurate motion and strain estimation.

}, doi = {http://dx.doi.org/10.1016/j.media.2015.05.001}, url = {http://www.sciencedirect.com/science/article/pii/S1361841515000687}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Johan G. Bosch and Santiago Aja-Fern{\'a}ndez} } @article {573, title = {Multiple Comparator Classifier Framework for Accelerometer-Based Fall Detection and Diagnostic}, journal = {Applied Soft Computing}, year = {2015}, month = {In press}, author = {Gibson, Ryan M and Amira, Abbes and Ramzan, Naeem and Pablo Casaseca-de-la-Higuera and Pervez, Zeeshan} } @conference {588, title = {Multiresolution Reconstruction of Real-Time MRI with Motion Compensated Compressed Sensing: Application to 2D Free-Breathing Cardiac MRI}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, year = {2015}, month = {11/2015}, address = {Madrid}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and Marcos Martin-Fernandez and Federico Simmross-Wattenberg and Claudia Prieto and Carlos Alberola-Lopez} } @article {533, title = {Non-Rigid Groupwise Registration for Motion Estimation and Compensation in Compressed Sensing Reconstruction of Breath-Hold Cardiac Cine MRI}, journal = {Magnetic Resonance in Medicine}, year = {2015}, doi = {10.1002/mrm.25733}, author = {J Royuela-del-Val and Lucilio Cordero-Grande and Federico Simmross-Wattenberg and Marcos Mart{\'\i}n-Fern{\'a}ndez and Carlos Alberola-Lopez} } @inbook {572, title = {PPG Beat Reconstruction Based on Shape Models and Probabilistic Templates for Signals Acquired with Conventional Smartphones}, booktitle = {Lecture Notes in Computer Science}, volume = {9117}, year = {2015}, pages = {595{\textendash}602}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Domingues, Alexandre and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez and Sanches, J Miguel} } @article {542, title = {Probabilistic Tissue Characterization for Ultrasound Images}, journal = {Insight Journal}, year = {2015}, abstract = {

This document describes the derivation of the mixture models commonly used in the literature to describe the probabilistic nature of speckle: The Gaussian Mixture Model, the Rayleigh Mixture Model, the Gamma Mixture Model and the Generalized Gamma Mixture Model. New algorithms were implemented using the Insight Toolkit
ITK for tissue characterization by means of a mixture model.


The source code is composed of a set of reusable ITK filters and classes. In addition to an overview of our implementation, we provide the source code, input data, parameters and output data that the authors used for validating the different probabilistic tissue characterization variants described in this paper. This adheres to the fundamental principle that scientific publications must facilitate reproducibility of the reported results.

}, url = {http://www.insight-journal.org/browse/publication/955}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @conference {520, title = {Single Breath Hold Whole Heart Cine MRI With Iterative Groupwise Cardiac Motion Compensation and Sparse Regularization (kt-WiSE)}, booktitle = {Proceedings of the International Society for Magnetic Resonance in Medicine 23}, year = {2015}, author = {J Royuela-del-Val and Muhammad Usman and Lucilio Cordero-Grande and Federico Simmross-Wattenberg and Marcos Martin-Fern{\'a}ndez and Claudia Prieto and Carlos Alberola-Lopez} } @article {568, title = {Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization}, journal = {PLoS ONE}, volume = {10}, year = {2015}, pages = {e0138910}, doi = {10.1371/journal.pone.0138910}, url = {http://dx.doi.org/10.1371\%2Fjournal.pone.0138910}, author = {Canales-Rodr{\'\i}guez, Erick J. and Daducci, Alessandro and Stamatios N. Sotiropoulos and Caruyer, Emmanuel and Santiago Aja-Fern{\'a}ndez and Radua, Joaquim and Yurramendi Mendizabal, Jes{\'u}s M. and Iturria-Medina, Yasser and Melie-Garc{\'\i}a, Lester and Alem{\'a}n-G{\'o}mez, Yasser and J-P Thiran and Sarr{\'o}, Salvador and Pomarol-Clotet, Edith and Salvador, Raymond} } @conference {589, title = {Tissue and Label Modelling for Segmentation of Scar with Contour Correction in Cardiac DE-CMR Volumes}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2015}, month = {11/2015}, address = {Madrid, Spain}, abstract = {Most scar segmentation methods for cardiac DE-CMR images are constrained by a previous myocardial segmentation that provides borders for the scar identification. However, the automation of these methods rely on an existing myocardial segmentation from CINE-CMR that is registered to the DE-CMR volume; in this step, however, alignment errors are usually introduced and they carry over to the labeling operation. These errors typically remain unchanged after tissue labeling, so inconsistencies between the two (alignment and labeling) may exist. We explore this issue and present a method that, with the same inputs, identifies the healthy and scarred tissue and selectively corrects the endocardial and epicardial contours depending on the image edges, the estimated probabilistic distributions and the proximity to the aligned myocardial borders. For this, we model the posterior probability of each ROI label with a Bayesian approach that unifies the prior tissue probabilities and the myocardial labels. The maximum a posteriori criterion is used to compute a first DE-CMR label map, which is afterwards refined by a connected component analysis. Preliminary results show better accuracy for the endocardial and epicardial contours, and the segmented scar compares favorably with respect to state of the art methods.}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and P{\'e}rez Rodr{\'\i}guez, M. T. and T. Sevilla-Ruiz and A. Revilla-Orodea and Mart{\'\i}n-Fern{\'a}ndez, M. and Carlos Alberola-Lopez} } @conference {656, title = {Tissue and Label Modelling for Segmentation of Scar with Contour Correction in Cardiac DE-CMR Volumes}, booktitle = {XXXIII Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2015}, month = {2015}, address = {Madrid, Spain}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and P{\'e}rez Rodr{\'\i}guez, M Teresa and T. Sevilla-Ruiz and A. Revilla-Orodea and Mart{\'\i}n-Fern{\'a}ndez, Marcos and Carlos Alberola-Lopez} } @article {534, title = {A local fuzzy thresholding methodology for multiregion image segmentation}, journal = {Knowledge-Based Systems}, volume = {83}, year = {2015}, month = {07/2015}, pages = {1-12}, abstract = {

Abstract Thresholding is a direct and simple approach to extract different regions from an image. In its basic formulation, thresholding searches for a global value that maximizes the separation between output classes. The use of a single hard threshold value is precisely the source of important segmentation errors in many scenarios like noisy images or uneven illumination. If no connectivity or closed objects are considered, the method is prone to produce isolated pixels. In this paper a new multiregion thresholding methodology is presented to overcome the common drawbacks of thresholding methods when images are corrupted with artifacts and noise. It is based on relating each pixel in the image to different output centroids via a fuzzy membership function, avoiding any initial hard decision. The starting point of the technique is the definition of the output centroids using a clustering method compatible with most thresholding techniques in the literature. The method makes use of the spatial information through a local aggregation step where the membership degree of each pixel is modified by local information that takes into account the memberships of the surrounding pixels. This makes the method robust to noise and artifacts. The general formulation of the proposed methodology allows the design of spatial aggregations for multiple applications, including the possibility of including heuristic information via a fuzzy inference rule base.

}, issn = {0950-7051}, doi = {http://dx.doi.org/10.1016/j.knosys.2015.02.029}, url = {http://www.sciencedirect.com/science/article/pii/S095070511500129X}, author = {Santiago Aja-Fern{\'a}ndez and Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @proceedings {516, title = {Analysis of coloured noise in received signal strength using the Allan Variance}, volume = {22}, year = {2014}, pages = {994-998}, publisher = {IEEE}, author = {Luo, Chunbo and Pablo Casaseca-de-la-Higuera and McClean, Sally and Parr, Gerard and Grecos, Christos} } @article {martin2014automatic, title = {Automatic detection of wakefulness and rest intervals in actigraphic signals: A data-driven approach}, journal = {Medical engineering \& physics}, volume = {36}, number = {12}, year = {2014}, pages = {1585{\textendash}1592}, publisher = {Elsevier}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Jesus Maria Andres-de-Llano and Jose Ramon Garmendia-Leiza and Susana Alberola-Lopez and Carlos Alberola-Lopez} } @article {curiale2014fully, title = {Fully Automatic Detection of Salient Features in 3-D Transesophageal Images}, journal = {Ultrasound in medicine \& biology}, volume = {40}, year = {2014}, month = {07/2014}, pages = {2868-2884}, publisher = {Elsevier}, chapter = {2868}, author = {Ariel H. Curiale and Haak, Alexander and Gonzalo Vegas-S{\'a}nchez-Ferrero and Ren, Ben and Santiago Aja-Fern{\'a}ndez and Johan G. Bosch} } @conference {571, title = {HLS based hardware acceleration on the zynq SoC: A case study for fall detection system}, booktitle = {IEEE/ACS 11th International Conference on Computer Systems and Applications (AICCSA 2014)}, year = {2014}, address = {Doha, Qatar}, author = {Ait Si Ali, Amine and Siupik, Marek and Amira, Abbes and Bensaali, Faycal and Pablo Casaseca-de-la-Higuera} } @conference {426, title = {MOWHARP: Multi-Oriented Windowed HARP Reconstruction for Robust Strain Imaging}, booktitle = {Proceedings of the International Society for Magnetic Resonance in Medicine 22}, year = {2014}, author = {Lucilio Cordero-Grande and J Royuela-del-Val and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {445, title = {Multi-stencil streamline fast marching: a general 3D framework to determine myocardial thickness and transmurality in late enhancement images}, journal = {Medical Imaging, IEEE Transactions on}, volume = {33}, year = {2014}, pages = {23{\textendash}37}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and A. Revilla-Orodea and Perez, M. T. and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {canales2014spherical, title = {Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and total variation spatial regularization}, journal = {arXiv preprint arXiv:1410.6353}, year = {2014}, author = {Canales-Rodr{\'\i}guez, Erick J and Daducci, Alessandro and Stamatios N. Sotiropoulos and Caruyer, Emmanuel and Santiago Aja-Fern{\'a}ndez and Radua, Joaquim and Mendizabal, Yosu Yurramendi and Iturria-Medina, Yasser and Melie-Garc{\'\i}a, Lester and Alem{\'a}n-G{\'o}mez, Yasser} } @conference {570, title = {An efficient user-customisable multiresolution classifier fall detection and diagnostic system}, booktitle = {26th IEEE International Conference on Microelectronics (ICM 2014)}, year = {2014}, address = {Doha, Qatar}, author = {Gibson, Ryan M and Amira, Abbes and Pablo Casaseca-de-la-Higuera and Ramzan, Naeem and Pervez, Zeeshan} } @conference {447, title = {A stochastic modelling framework for the reconstruction of cardiovascular signals}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE}, volume = {36}, year = {2014}, pages = {676-679}, publisher = {IEEE}, organization = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Amira, Abbes and Luo, Chunbo and Grecos, Christos and Carlos Alberola-Lopez} } @conference {444, title = {Assessment of the fibrotic myocardial tissue mechanics by image processing}, booktitle = {Computing in Cardiology Conference (CinC), 2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, author = {Lucilio Cordero-Grande and T. Sevilla-Ruiz and Revilla, Ana and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {443, title = {Classification of delayed enhancement scar islands by means of their local subendocardial transmurality}, booktitle = {Computing in Cardiology Conference (CinC), 2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and T. Sevilla-Ruiz and P{\'e}rez, Teresa and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @proceedings {martin2014ecg, title = {ECG Signal Reconstruction Based on Stochastic Joint-Modeling of the ECG and the PPG Signals}, year = {2013}, pages = {989{\textendash}992}, publisher = {Springer International Publishing}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {cordero2013groupwise, title = {Groupwise elastic registration by a new sparsity-promoting metric: application to the alignment of cardiac magnetic resonance perfusion images}, journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on}, volume = {35}, number = {11}, year = {2013}, pages = {2638{\textendash}2650}, publisher = {IEEE}, author = {Lucilio Cordero-Grande and S. Merino-Caviedes and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {garmendia2013influence, title = {Influence of institutionalization on the sleep pattern in elderly population}, journal = {Sleep Medicine}, volume = {14}, year = {2013}, pages = {e181{\textendash}e182}, publisher = {Elsevier}, author = {Jose Ramon Garmendia-Leiza and Aguilar Garcia, M and Jes{\'u}s Mar{\'\i}a And De Llano and Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @conference {cordero2013integration, title = {Integration of biomechanical properties in a Markov random field: Application to myocardial motion estimation in cardiomyopathy patients}, booktitle = {Quantitative Medical Imaging}, year = {2013}, pages = {QW2G{\textendash}1}, publisher = {Optical Society of America}, organization = {Optical Society of America}, author = {Lucilio Cordero-Grande and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {446, title = {Probabilistic modeling of the oxygen saturation pattern for the detection of anomalies during clinical interventions}, booktitle = {Computing in Cardiology Conference (CinC), 2013}, year = {2013}, publisher = {IEEE}, organization = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Mart{\'\i}n-Fern{\'a}ndez, M and Carlos Alberola-Lopez} } @conference {aja2013robust, title = {Robust estimation of MRI myocardial perfusion parameters}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE}, year = {2013}, pages = {4382{\textendash}4385}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Rodrigo de Luis-Garc{\'\i}a and Carlos Alberola-Lopez} } @inbook {curiale2013speckle, title = {Speckle tracking in interpolated echocardiography to estimate heart motion}, booktitle = {Functional Imaging and Modeling of the Heart}, year = {2013}, pages = {325{\textendash}333}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Santiago Aja-Fern{\'a}ndez} } @article {martin2013stochastic, title = {Stochastic Modeling of the PPG Signal: A Synthesis-by-Analysis Approach With Applications}, journal = {Biomedical Engineering, IEEE Transactions on}, volume = {60}, number = {9}, year = {2013}, pages = {2432{\textendash}2441}, publisher = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {curiale2013strain, title = {Strain rate tensor estimation from echocardiography for quantitative assessment of functional mitral regurgitation}, booktitle = {Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on}, year = {2013}, pages = {788{\textendash}791}, publisher = {IEEE}, organization = {IEEE}, author = {Ariel H. Curiale and Gonzalo Vegas-S{\'a}nchez-Ferrero and Teresa P{\'e}rez-Sanz and Santiago Aja-Fern{\'a}ndez} } @article {martin2013utility, title = {Utility of the statistical and nonlinear analysis for the actigraphic sleep pattern characterization}, journal = {Sleep Medicine}, volume = {14}, year = {2013}, pages = {e181}, publisher = {Elsevier}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez and Jose Ramon Garmendia-Leiza and Jes{\'u}s Mar{\'\i}a And De Llano and Susana Alberola Lopez} } @article {cordero2013magnetic, title = {A magnetic resonance software simulator for the evaluation of myocardial deformation estimation}, journal = {Medical engineering \& physics}, volume = {35}, number = {9}, year = {2013}, pages = {1331{\textendash}1340}, publisher = {Elsevier}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez} } @conference {cordero20123d, title = {3D fusion of cine and late-enhanced cardiac magnetic resonance images}, booktitle = {Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on}, year = {2012}, pages = {286{\textendash}289}, publisher = {IEEE}, organization = {IEEE}, author = {Lucilio Cordero-Grande and S. Merino-Caviedes and Alba, X{\`e}nia and Figueras i Ventura, RM and Frangi, Alejandro F and Carlos Alberola-Lopez} } @conference {casaseca2012automatic, title = {Automatic diagnosis of ADHD based on multichannel nonlinear analysis of actimetry registries}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE}, year = {2012}, pages = {4204{\textendash}4207}, publisher = {IEEE}, organization = {IEEE}, author = {Pablo Casaseca-de-la-Higuera and Diego Mart{\'\i}n-Mart{\'\i}nez and Susana Alberola-Lopez and Jesus Maria Andres-de-Llano and L{\'o}pez-Villalobos, Jos{\'e} Antonio and JR Garmendia-Leiza and Carlos Alberola-Lopez} } @conference {martin2012cardiovascular, title = {Cardiovascular signal reconstruction based on shape modelling and non-stationary temporal modelling}, booktitle = {Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European}, year = {2012}, pages = {1826{\textendash}1830}, publisher = {IEEE}, organization = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {462, title = {Detecci{\'o}n autom{\'a}tica del ventr{{\'\i}culo derecho en im{\'a}genes de resonancia magn{\'e}tica cardiaca 3D}, booktitle = {CASEIB2012, San Sebasti{\'a}n, Espana}, year = {2012}, author = {D{\'\i}az-Rodr{\'\i}guez, JM and Lucilio Cordero-Grande and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {aja2012mri, title = {A MRI phantom for cardiac perfusion simulation}, booktitle = {Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on}, year = {2012}, pages = {638{\textendash}641}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Lucilio Cordero-Grande and Carlos Alberola-Lopez} } @article {cordero2012markov, title = {A Markov random field approach for topology-preserving registration: Application to object-based tomographic image interpolation}, journal = {Image Processing, IEEE Transactions on}, volume = {21}, number = {4}, year = {2012}, pages = {2047{\textendash}2061}, publisher = {IEEE}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @proceedings {580, title = {M{\'e}todos de an{\'a}lisis autom{\'a}tico de la actividad diaria del ni{\~n}o con TDAH. Mesa Redonda. Ponencia Invitada}, volume = {61}, year = {2012}, pages = {43-49}, address = {Granada, Spain}, author = {Pablo Casaseca-de-la-Higuera and Diego Mart{\'\i}n-Mart{\'\i}nez and Susana Alberola-Lopez and Jesus Maria Andres-de-Llano and L{\'o}pez-Villalobos, Jos{\'e} Antonio and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @article {martin2012nonlinear, title = {Nonlinear analysis of actigraphic signals for the assessment of the attention-deficit/hyperactivity disorder (ADHD)}, journal = {Medical engineering \& physics}, volume = {34}, number = {9}, year = {2012}, pages = {1317{\textendash}1329}, publisher = {Elsevier}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Susana Alberola-Lopez and Jesus Maria Andres-de-Llano and L{\'o}pez-Villalobos, JA and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @article {casaseca2012optimal, title = {Optimal real-time estimation in diffusion tensor imaging}, journal = {Magnetic resonance imaging}, volume = {30}, number = {4}, year = {2012}, pages = {506{\textendash}517}, publisher = {Elsevier}, author = {Pablo Casaseca-de-la-Higuera and Antonio Trist{\'a}n-Vega and Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Carl-Fredik Westin and Raul San Jose-Estepar} } @inbook {cardenes2012quantitative, title = {Quantitative Analysis of Pyramidal Tracts in Brain Tumor Patients Using Diffusion Tensor Imaging}, booktitle = {Tumors of the Central Nervous System, Volume 4}, year = {2012}, pages = {143{\textendash}152}, publisher = {Springer Netherlands}, organization = {Springer Netherlands}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Sarabia-Herrero, Rosario and Daniel Argibay-Qui{\~n}ones and Marcos Martin-Fernandez} } @proceedings {579, title = {Reconstrucci{\'o}n de la Se{\~n}al Respiratoria basada en Modelo Conjunto con la Se{\~n}al de Per{\'\i}odo Card{\'\i}aco}, year = {2012}, address = {San Sebasti{\'a}n, Spain}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Mart{\'\i}n-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {575, title = {Relation between Myocardial Infarction and Cyrcadian Rhythm in Patients Attended in a Prehospital Emergency Service}, journal = {Medicina Cl{\'\i}nica}, volume = {139}, year = {2012}, pages = {515-521}, chapter = {551}, author = {Barneto-Valero, Mar{\'\i}a Cristina and Jose Ramon Garmendia-Leiza and Julio Ardura-Fernández and Pablo Casaseca-de-la-Higuera and Jesus Maria Andres-de-Llano and Corral-Torres, Ervigio} } @proceedings {581, title = {TDAH en atenci{\'o}n primaria: Registro de la Actividad mediante actimetr{\'\i}a ambulatoria. Mesa Redonda. Ponencia Invitada}, volume = {61}, year = {2012}, pages = {34-39}, address = {Granada, Spain}, author = {Susana Alberola-Lopez and Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Irene Casares-Alonso and Isabel P{\'e}rez-Garc{\'\i}a and Alfredo Cano-Garcinu{\~n}o and L{\'o}pez-Villalobos, Jos{\'e} Antonio and Ruiz, F.C. and Jesus Maria Andres-de-Llano and Carlos Alberola-Lopez and Julio Ardura-Fernández} } @inbook {432, title = {Ubiquitous tele-monitoring kit (UTK): measuring physiological signals anywhere at anytime}, booktitle = {Ambient Assisted Living and Home Care}, year = {2012}, pages = {183{\textendash}191}, publisher = {Springer}, organization = {Springer}, author = {Marcos-Lagunar, Carlos and Cavero-Barca, Carlos and Quintero-Padr{\'o}n, Ana Mar{\'\i}a and Planes, Xavier and Federico Simmross-Wattenberg and Carlos Alberola-Lopez and Marcos Martin-Fernandez and Mart{\'\i}n-Hern{\'a}ndez, Noelia and Calder{\'o}n-Oliveras, Enric and Corral-Herranz, Javier and Gonz{\'a}lez-Mart{\'\i}nez, A. and Huguet, Jordi and Aguilar, Rosal{\'\i}a} } @proceedings {582, title = {Validez de los criterios DSM-IV en el diagnostico del TDAH. Nuevas perspectivas de investigaci{\'o}n. Mesa Redonda. Ponencia Invitada}, volume = {61}, year = {2012}, pages = {39-43}, address = {Granada, Spain}, author = {L{\'o}pez-Villalobos, Jos{\'e} Antonio and Jesus Maria Andres-de-Llano and Susana Alberola-Lopez and Pablo Casaseca-de-la-Higuera and Diego Mart{\'\i}n-Mart{\'\i}nez and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @proceedings {586, title = {Algoritmo de Compresi{\'o}n de Se{\~n}ales de ECG basado en un Modelo de S{\'\i}ntesis. An{\'a}lisis Comparativo}, volume = {29}, year = {2011}, pages = {733-736}, address = {C{\'a}ceres, Spain}, author = {V{\'\i}ctor Mart{\'\i}nez-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fern{\'a}ndez and Carlos Alberola-Lopez} } @article {193, title = {Anomaly detection in network traffic based on statistical inference and alpha-stable modeling}, journal = {Dependable and Secure Computing, IEEE Transactions on}, volume = {8}, year = {2011}, pages = {494{\textendash}509}, author = {Federico Simmross-Wattenberg and Juan Ignacio Asensio-P{\'e}rez and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Yannis A Dimitriadis and Carlos Alberola-Lopez} } @proceedings {576, title = {Automatic diagnosis of ADHD based on nonlinear analysis of actimetry registries}, volume = {32}, year = {2011}, pages = {685-688}, address = {Prague, Czech Rep.}, keywords = {ADHD, ADHD automatic diagnosis, Activity/Rest Detection, Attention-Deficit Hyperactivity Disorder, Automatic Diagnosis System, Central Tendency Measure, Feature extraction, Histograms, Indexes, Noise, Pediatrics, Regularity Assessment, Sleep, USA Councils, Wrist, actimetry registries, adolescence, automatic activity/rest detection filter, biomedical measurement, childhood, feature extraction module, medical disorders, medical signal processing, mental health problem, neurophysiology, nonlinear analysis, nonlinear regularity quantification, paediatrics, pathology, signal processing methods}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Susana Alberola-Lopez and L{\'o}pez-Villalobos, J.A. and Ruiz, F.C. and Jesus Maria Andres-de-Llano and Jose Ramon Garmendia-Leiza and Julio Ardura-Fernández} } @article {garmendia2011beta, title = {Beta blocker therapy modifies circadian rhythm acute myocardial infarction}, journal = {International journal of cardiology}, volume = {147}, number = {2}, year = {2011}, pages = {316{\textendash}317}, publisher = {Elsevier}, author = {Jose Ramon Garmendia-Leiza and Jesus Maria Andres-de-Llano and Julio Ardura-Fernández and Juan Bautista Lopez-Messa and Carlos Alberola-Lopez and Pablo Casaseca-de-la-Higuera} } @conference {405, title = {Cuantificaci{\'o}n de la insuficiencia mitral funcional mediante el esfuerzo y la velocidad del miocardio}, booktitle = {XXIX Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, year = {2011}, address = {Centro de Cirug{\'\i}a de M{\'\i}nima Invasi{\'o}n Jes{\'u}s Us{\'o}n}, author = {Ariel H. Curiale and S{\'a}nchez-Ferrero, G Vegas and Teresa P{\'e}rez-Sanz and Santiago Aja-Fern{\'a}ndez} } @conference {arenillas2011diffusion, title = {Diffusion Tensor Imaging (DTI) Monitoring Of Motor Function Recovery After Middle Cerebral Artery Infarction: Searching For A DTI-Marker Of Neurorepair}, booktitle = {STROKE}, volume = {42}, number = {3}, year = {2011}, pages = {E119{\textendash}E119}, publisher = {LIPPINCOTT WILLIAMS \& WILKINS 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA}, organization = {LIPPINCOTT WILLIAMS \& WILKINS 530 WALNUT ST, PHILADELPHIA, PA 19106-3621 USA}, author = {Juan F Arenillas and Daniel Argibay-Qui{\~n}ones and Garcia-Bermejo, Pablo and Calleja, Ana I and Diego Mart{\'\i}n-Mart{\'\i}nez and Jose M Sierra and Juan Jos{\'e} Fuertes-Alija and Marcos Martin-Fernandez} } @proceedings {cordero2011groupwise, title = {Groupwise myocardial alignment in magnetic resonance perfusion sequences}, year = {2011}, pages = {437{\textendash}440}, author = {Lucilio Cordero-Grande and S. Merino-Caviedes and Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {cordero2011improving, title = {Improving Harmonic Phase Imaging by the Windowed Fourier Transform}, booktitle = {Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on}, year = {2011}, pages = {520{\textendash}523}, publisher = {IEEE}, organization = {IEEE}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @conference {585, title = {Intra Heartbeat Variability as a Tool for Cardiovascular Diagnosis and Monitoring}, booktitle = {XXIX Congreso Anual de la Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica (CASEIB)}, volume = {29}, year = {2011}, pages = {343-346}, address = {C{\'a}ceres, Spain}, author = {Daniel Ruiz-Aguado and Marcos Martin-Fern{\'a}ndez and J Royuela-del-Val and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @proceedings {584, title = {Modelado Estad{\'\i}stico de Se{\~n}ales Fotopletismogr{\'a}ficas para la Construcci{\'o}n de Atlas Poblacionales Orientados a la Evaluaci{\'o}n y Seguimiento del Remodelado Cardiovascular}, volume = {29}, year = {2011}, pages = {607-610}, address = {C{\'a}ceres, Spain}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Mart{\'\i}n Fern{\'a}ndez, Marcos and Carlos Alberola-Lopez} } @conference {vegas2011realistic, title = {Realistic log-compressed law for ultrasound image recovery}, booktitle = {Image Processing (ICIP), 2011 18th IEEE International Conference on}, year = {2011}, pages = {2029{\textendash}2032}, publisher = {IEEE}, organization = {IEEE}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Lucilio Cordero-Grande and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Cesar Palencia} } @inbook {cordero2011topology, title = {Topology-preserving registration: a solution via graph cuts}, booktitle = {Combinatorial Image Analysis}, year = {2011}, pages = {420{\textendash}431}, publisher = {Springer}, organization = {Springer}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Carlos Alberola-Lopez} } @proceedings {merino2011transmurality, title = {Transmurality Maps in Late Enhancement Cardiac Magnetic Resonance Imaging by a New Radial Fast Marching Method}, year = {2011}, pages = {211{\textendash}214}, author = {S. Merino-Caviedes and Lucilio Cordero-Grande and P{\'e}rez, M Teresa and Marcos Martin-Fernandez} } @article {cordero2011unsupervised, title = {Unsupervised 4D myocardium segmentation with a Markov Random Field based deformable model}, journal = {Medical image analysis}, volume = {15}, number = {3}, year = {2011}, pages = {283{\textendash}301}, publisher = {Elsevier}, author = {Lucilio Cordero-Grande and Gonzalo Vegas-S{\'a}nchez-Ferrero and Pablo Casaseca-de-la-Higuera and Alberto San-Rom{\'a}n-Calvar, J and A. Revilla-Orodea and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {cardenes2010analysis, title = {Analysis of the pyramidal tract in tumor patients using diffusion tensor imaging}, journal = {NeuroImage}, volume = {50}, number = {1}, year = {2010}, pages = {27{\textendash}39}, publisher = {Elsevier}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Sarabia-Herrero, Rosario and Rodr{\'\i}guez-Velasco, Margarita and Juan Jos{\'e} Fuertes-Alija and Marcos Martin-Fernandez} } @article {423, title = {Automatic bayesian classification of healthy controls, bipolar disorder, and schizophrenia using intrinsic connectivity maps from fMRI data}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {57}, year = {2010}, pages = {2850-2860}, abstract = {

We present a method for supervised, automatic, and reliable classification of healthy controls, patients with bipolar disorder, and patients with schizophrenia using brain imaging data. The method uses four supervised classification learning machines trained with a stochastic gradient learning rule based on the minimization of KullbackLeibler divergence and an optimal model complexity search through posterior probability estimation. Prior to classification, given the high dimensionality of functional MRI (fMRI) data, a dimension reduction stage comprising two steps is performed: first, a one-sample univariate t-test mean-difference Tscore approach is used to reduce the number of significant discriminative functional activated voxels, and then singular value decomposition is performed to further reduce the dimension of the input patterns to a number comparable to the limited number of subjects available for each of the three classes. Experimental results using functional brain imaging (fMRI) data include receiver operation characteristic curves for the three-way classifier with area under curve values around 0.82, 0.89, and 0.90 for healthy control versus nonhealthy, bipolar disorder versus nonbipolar, and schizophrenia patients versus nonschizophrenia binary problems, respectively. The average three-way correct classification rate (CCR) is in the range of 70\%-72\%, for the test set, remaining close to the estimated Bayesian optimal CCR theoretical upper bound of about 80\%, estimated from the one nearest-neighbor classifier over the same data. {\^A}{\textcopyright} 2010 IEEE.

}, keywords = {Algorithms, Artificial Intelligence, Bayes Theorem, Bayesian learning, Bayesian networks, Biological, Brain, Case-Control Studies, Classifiers, Computer-Assisted, Diseases, Functional MRI (fMRI), Humans, Learning machines, Learning systems, Magnetic Resonance Imaging, Models, Operation characteristic, Optimization, ROC Curve, Reproducibility of Results, Signal Processing, Singular value decomposition, Statistical tests, Stochastic models, Student t test, area under the curve, article, bipolar disorder, classification, controlled study, functional magnetic resonance imaging, human, machine learning, major clinical study, neuroimaging, patient coding, receiver operating characteristic, reliability, schizophrenia}, issn = {00189294}, doi = {10.1109/TBME.2010.2080679}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-78649311169\&partnerID=40\&md5=d3b90f1a3ee4ef209d131ef986e142db}, author = {J I Arribas and V D Calhoun and T Adali} } @proceedings {515, title = {Characterization of activity epochs in actimetric registries for infantile colic diagnosis: Identification and feature extraction based on wavelets and symbolic dynamics}, volume = {32}, year = {2010}, pages = {2383-2386}, publisher = {IEEE}, author = {Diego Mart{\'\i}n-Mart{\'\i}nez and Pablo Casaseca-de-la-Higuera and Gonzalo Vegas-S{\'a}nchez-Ferrero and Lucilio Cordero-Grande and Jesus Maria Andres-de-Llano and Jose Ramon Garmendia-Leiza and Julio Ardura-Fernández} } @conference {aja2010dwi, title = {DWI acquisition schemes and diffusion tensor estimation: a simulation-based study}, booktitle = {Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE}, year = {2010}, pages = {3317{\textendash}3320}, publisher = {IEEE}, organization = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Pablo Casaseca-de-la-Higuera} } @article {cardenes2010fast, title = {Fast and accurate geodesic distance transform by ordered propagation}, journal = {Image and Vision Computing}, volume = {28}, number = {3}, year = {2010}, pages = {307{\textendash}316}, publisher = {Elsevier}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @article {cardenes2010saturn, title = {Saturn: A software application of tensor utilities for research in neuroimaging}, journal = {Computer methods and programs in biomedicine}, volume = {97}, number = {3}, year = {2010}, pages = {264{\textendash}279}, publisher = {Elsevier}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Antonio Trist{\'a}n-Vega and Marcos Martin-Fernandez} } @article {martin2009addendum, title = {Addendum to {\textquotedblleft}Sequential anisotropic multichannel Wiener filtering with Rician bias correction applied to 3D regularization of DWI data{\textquotedblright}[Medical Image Analysis 13 (2009) 19{\textendash}35]}, journal = {Medical image analysis}, volume = {13}, number = {6}, year = {2009}, pages = {910}, publisher = {Elsevier}, author = {Marcos Martin-Fernandez and Emma Mu{\~n}oz-Moreno and Cammoun, Leila and J-P Thiran and Carl-Fredik Westin and Carlos Alberola-Lopez} } @article {martin2009automatic, title = {Automatic articulated registration of hand radiographs}, journal = {Image and Vision Computing}, volume = {27}, number = {8}, year = {2009}, pages = {1207{\textendash}1222}, publisher = {Elsevier}, author = {Miguel Angel Martin-Fernandez and Rub{\'e}n C{\'a}rdenes-Almeida and Emma Mu{\~n}oz-Moreno and Rodrigo de Luis-Garc{\'\i}a and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {cardenes2009characterization, title = {Characterization of anatomic fiber bundles for diffusion tensor image analysis}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2009}, year = {2009}, pages = {903{\textendash}910}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Daniel Argibay-Qui{\~n}ones and Emma Mu{\~n}oz-Moreno and Marcos Martin-Fernandez} } @inbook {munoz2009review, title = {Review of techniques for registration of diffusion tensor imaging}, booktitle = {Tensors in Image Processing and Computer Vision}, year = {2009}, pages = {273{\textendash}297}, publisher = {Springer London}, organization = {Springer London}, author = {Emma Mu{\~n}oz-Moreno and Rub{\'e}n C{\'a}rdenes-Almeida and Marcos Martin-Fernandez} } @article {martin2009sequential, title = {Sequential anisotropic multichannel Wiener filtering with Rician bias correction applied to 3D regularization of DWI data}, journal = {Medical image analysis}, volume = {13}, number = {1}, year = {2009}, pages = {19{\textendash}35}, publisher = {Elsevier}, author = {Marcos Martin-Fernandez and Emma Mu{\~n}oz-Moreno and Cammoun, Leila and J-P Thiran and Carl-Fredik Westin and Carlos Alberola-Lopez} } @inbook {brun2009similar, title = {Similar Tensor Arrays{\textendash}A Framework for Storage of Tensor Array Data}, booktitle = {Tensors in Image Processing and Computer Vision}, year = {2009}, pages = {407{\textendash}428}, publisher = {Springer London}, organization = {Springer London}, author = {Brun, Anders and Marcos Martin-Fernandez and Acar, Burak and Emma Mu{\~n}oz-Moreno and Cammoun, Leila and Sigfridsson, Andreas and Dario Sosa-Cabrera and Svensson, Bj{\"o}rn and Herberthson, Magnus and Knutsson, Hans} } @article {casaseca2009multichannel, title = {A multichannel model-based methodology for extubation readiness decision of patients on weaning trials}, journal = {Biomedical Engineering, IEEE Transactions on}, volume = {56}, number = {7}, year = {2009}, pages = {1849{\textendash}1863}, publisher = {IEEE}, author = {Pablo Casaseca-de-la-Higuera and Federico Simmross-Wattenberg and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @article {477, title = {A multidimensional segmentation evaluation for medical image data}, journal = {Computer methods and programs in biomedicine}, volume = {96}, year = {2009}, pages = {108{\textendash}124}, abstract = {

Evaluation of segmentation methods is a crucial aspect in image processing, especially in the medical imaging field, where small differences between segmented regions in the anatomy can be of paramount importance. Usually, segmentation evaluation is based on a measure that depends on the number of segmented voxels inside and outside of some reference regions that are called gold standards. Although some other measures have been also used, in this work we propose a set of new similarity measures, based on different features, such as the location and intensity values of the misclassified voxels, and the connectivity and the boundaries of the segmented data. Using the multidimensional information provided by these measures, we propose a new evaluation method whose results are visualized applying a Principal Component Analysis of the data, obtaining a simplified graphical method to compare different segmentation results. We have carried out an intensive study using several classic segmentation methods applied to a set of MRI simulated data of the brain with several noise and RF inhomogeneity levels, and also to real data, showing that the new measures proposed here and the results that we have obtained from the multidimensional evaluation, improve the robustness of the evaluation and provides better understanding about the difference between segmentation methods.

}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Rodrigo de Luis-Garc{\'\i}a and Bach-Cuadra, Meritxell} } @proceedings {simmross2008modelling, title = {Modelling Network Traffic as alpha-Stable Stochastic Processes: An Approach Towards Anomaly Detection}, year = {2008}, pages = {25{\textendash}32}, author = {Federico Simmross-Wattenberg and Antonio Trist{\'a}n-Vega and Pablo Casaseca-de-la-Higuera and Juan Ignacio Asensio-P{\'e}rez and Marcos Martin-Fernandez and Yannis A Dimitriadis and Carlos Alberola-Lopez} } @conference {vegas2008strain, title = {Strain Rate Tensor estimation in cine cardiac MRI based on elastic image registration}, booktitle = {Computer Vision and Pattern Recognition Workshops, 2008. CVPRW{\textquoteright}08. IEEE Computer Society Conference on}, year = {2008}, pages = {1{\textendash}6}, publisher = {IEEE}, organization = {IEEE}, author = {Gonzalo Vegas-S{\'a}nchez-Ferrero and Antonio Trist{\'a}n-Vega and Lucilio Cordero-Grande and Pablo Casaseca-de-la-Higuera and Santiago Aja-Fern{\'a}ndez and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @proceedings {433, title = {On the estimation of joint probability density functions for multi-modal registration of medical images}, volume = {26}, year = {2008}, pages = {13-16}, publisher = {Sociedad Espa{\~n}ola de Ingenier{\'\i}a Biom{\'e}dica}, address = {Valladolid, Spain}, author = {Antonio Trist{\'a}n-Vega and Federico Simmross-Wattenberg and Emma Mu{\~n}oz-Moreno and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez} } @conference {de2007p6d, title = {Analysis of Ultrasound Images Based on Local Statistics. Application to the Diagnosis of Developmental Dysplasia of the Hip}, booktitle = {Ultrasonics Symposium, 2007. IEEE}, year = {2007}, pages = {2531{\textendash}2534}, publisher = {IEEE}, organization = {IEEE}, author = {Rodrigo de Luis-Garc{\'\i}a and Santiago Aja-Fern{\'a}ndez and Rub{\'e}n C{\'a}rdenes-Almeida and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @conference {480, title = {Multimodal evaluation for medical image segmentation}, booktitle = {Computer Analysis of Images and Patterns}, year = {2007}, publisher = {Springer}, organization = {Springer}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Bach, Meritxell and Chi, Ying and Marras, Ioannis and Rodrigo de Luis-Garc{\'\i}a and Anderson, Mats and Cashman, Peter and Bultelle, Matthieu} } @conference {martin2007parameter, title = {Parameter Estimation of the Homodyned K Distribution Based on Signal to Noise Ratio}, booktitle = {Ultrasonics Symposium, 2007. IEEE}, year = {2007}, pages = {158{\textendash}161}, publisher = {IEEE}, organization = {IEEE}, author = {Marcos Martin-Fernandez and Rub{\'e}n C{\'a}rdenes-Almeida and Carlos Alberola-Lopez} } @article {martin2007techniques, title = {Techniques in the contour detection of kidneys and their applications}, journal = {World Scientific Publishing Company}, year = {2007}, pages = {381{\textendash}398}, author = {Marcos Martin-Fernandez and Lucilio Cordero-Grande and Emma Mu{\~n}oz-Moreno and Carlos Alberola-Lopez} } @proceedings {cardenes2007usimagtool, title = {Usimagtool: an open source freeware software for ultrasound imaging and elastography}, year = {2007}, pages = {117{\textendash}127}, author = {Rub{\'e}n C{\'a}rdenes-Almeida and Antonio Trist{\'a}n-Vega and Ferrero, GVS and Santiago Aja-Fern{\'a}ndez} } @conference {cordero2006endocardium, title = {Endocardium and epicardium contour modeling based on Markov random fields and active contours}, booktitle = {Engineering in Medicine and Biology Society, 2006. EMBS{\textquoteright}06. 28th Annual International Conference of the IEEE}, year = {2006}, pages = {928{\textendash}931}, publisher = {IEEE}, organization = {IEEE}, author = {Lucilio Cordero-Grande and Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {421, title = {Estimation of Posterior Probabilities with Neural Networks: Application to Microcalcification Detection in Breast Cancer Diagnosis}, booktitle = {Handbook of Neural Engineering}, year = {2006}, pages = {41-58}, publisher = {John Wiley \& Sons, Inc.}, organization = {John Wiley \& Sons, Inc.}, isbn = {9780470056691}, doi = {10.1002/9780470068298.ch3}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-42249107409\&partnerID=40\&md5=aac6237961cec1a48c0e843a9a1912a4}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and Carlos Alberola-Lopez} } @article {casaseca2006weaning, title = {Weaning from mechanical ventilation: a retrospective analysis leading to a multimodal perspective}, journal = {Biomedical Engineering, IEEE Transactions on}, volume = {53}, number = {7}, year = {2006}, pages = {1330{\textendash}1345}, publisher = {IEEE}, author = {Pablo Casaseca-de-la-Higuera and Marcos Martin-Fernandez and Carlos Alberola-Lopez} } @inbook {arribas2005estimation, title = {Estimation of Posterior Probabilities with Neural Networks: Application to Microcalcification Detection in Breast Cancer Diagnosis}, booktitle = {Handbook of Neural Engineering}, year = {2005}, pages = {41{\textendash}58}, publisher = {Wiley Online Library}, organization = {Wiley Online Library}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and Carlos Alberola-Lopez} } @article {palacios2005group, title = {Group-Slicer: A collaborative extension of 3D-Slicer}, journal = {Journal of Biomedical Informatics}, volume = {38}, year = {2005}, pages = {431{\textendash}442}, author = {Federico Simmross-Wattenberg and Palacios-Camarero, Cristina and Pablo Casaseca-de-la-Higuera and Miguel Angel Martin-Fernandez and Santiago Aja-Fern{\'a}ndez and Juan Ruiz-Alzola and Carl-Fredik Westin and Carlos Alberola-Lopez} } @article {munoz2005image, title = {Image registration based on automatic detection of anatomical landmarks for bone age assessment}, journal = {WSEAS Transactions on Computers}, volume = {4}, number = {11}, year = {2005}, pages = {1596{\textendash}1603}, author = {Emma Mu{\~n}oz-Moreno and Rub{\'e}n C{\'a}rdenes-Almeida and Rodrigo de Luis-Garc{\'\i}a and Miguel Angel Martin-Fernandez and Carlos Alberola-Lopez} } @conference {429, title = {Weaning from mechanical ventilation: feature extraction from a statistical signal processing viewpoint}, booktitle = {Proc. 13th Signal Processing Conf., EUSIPCO}, year = {2005}, author = {Pablo Casaseca-de-la-Higuera and Rodrigo de Luis-Garc{\'\i}a and Federico Simmross-Wattenberg and Carlos Alberola-Lopez} } @proceedings {casaseca2006comparative, title = {A comparative study on microcalcification detection methods with posterior probability estimation based on Gaussian mixture models}, year = {2005}, pages = {49{\textendash}54}, publisher = {IEEE}, abstract = {Automatic detection of microcalcifications in mammograms constitutes a helpful tool in breast cancer diagnosis. Radiologist{\textquoteright}s confidence level on microcalcification detection would be improved if a probability estimate of its presence could be obtained from computer-aided diagnosis. In this paper we explore detection performance of a simple Bayesian classifier based on Gaussian mixture probability density functions (pdf). Posterior probability of microcalcification presence may be estimated from the probabilistic model. Two model selection algorithms have been tested, one based on the minimum message length criterion and the other on discriminative criteria obtained from the classifier performance. In addition, we propose a complementing model selection algorithm in order to improve the initial system performance obtained with these methods. Simulation results show that our model gets a good compromise between classification performance and probability estimation accuracy}, doi = {https://doi.org/10.1109/IEMBS.2005.1616339}, url = {https://ieeexplore.ieee.org/abstract/document/1616339}, author = {Pablo Casaseca-de-la-Higuera and J I Arribas and Emma Mu{\~n}oz-Moreno and Carlos Alberola L{\'o}pez} } @article {420, title = {A model selection algorithm for a posteriori probability estimation with neural networks}, journal = {IEEE Transactions on Neural Networks}, volume = {16}, year = {2005}, pages = {799-809}, abstract = {

This paper proposes a novel algorithm to jointly determine the structure and the parameters of a posteriori probability model based on neural networks (NNs). It makes use of well-known ideas of pruning, splitting, and merging neural components and takes advantage of the probabilistic interpretation of these components. The algorithm, so called a posteriori probability model selection (PPMS), is applied to an NN architecture called the generalized softmax perceptron (GSP) whose outputs can be understood as probabilities although results shown can be extended to more general network architectures. Learning rules are derived from the application of the expectation-maximization algorithm to the GSP-PPMS structure. Simulation results show the advantages of the proposed algorithm with respect to other schemes. {\^A}{\textcopyright} 2005 IEEE.

}, keywords = {Algorithms, Automated, Biological, Breast Neoplasms, Computer simulation, Computer-Assisted, Computing Methodologies, Decision Support Techniques, Diagnosis, Estimation, Expectation-maximization, Generalized Softmax Perceptron (GSP), Humans, Mathematical models, Model selection, Models, Neural Networks (Computer), Neural networks, Numerical Analysis, Objective function, Pattern recognition, Posterior probability, Probability, Statistical, Stochastic Processes, algorithm, article, artificial neural network, automated pattern recognition, biological model, breast tumor, classification, cluster analysis, computer analysis, computer assisted diagnosis, decision support system, evaluation, human, mathematical computing, methodology, statistical model, statistics}, issn = {10459227}, doi = {10.1109/TNN.2005.849826}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-23044459586\&partnerID=40\&md5=f00e7d86a625cfc466373a2a938276d0}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro} } @conference {arribas2003neural, title = {Neural posterior probabilities for microcalcification detection in breast cancer diagnoses}, booktitle = {Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on}, year = {2003}, pages = {660{\textendash}663}, publisher = {IEEE}, organization = {IEEE}, abstract = {We apply the a Posteriori Probability Model Selection (PPMS) algorithm with the help of Generalized Softmax Perceptron (GSP) neural architecture in order to obtain estimates of the posterior class probabilities at its outputs, in the binary problem of microcalcification detection in a hospital digitalized mammogram database. We first detect windowed images with high probability to belong to the class microcalcification is present, then we locally segment the shape of the calcifications, and finally show the segmented microcalcifications to the radiologist. The segmented images together with the posterior probabilities for each window image can be employed as a valuable information to help predicting a breast diagnosis, in order to distinguish between benignant calcium deposit and malignant accumulation, that is, breast carcinoma.}, doi = {https://doi.org/10.1109/CNE.2003.1196915}, url = {https://ieeexplore.ieee.org/abstract/document/1196915}, author = {J I Arribas and Carlos Alberola L{\'o}pez and Mateos-Marcos, A and Jes{\'u}s Cid-Sueiro} } @article {san2003theoretical, title = {A theoretical framework to three-dimensional ultrasound reconstruction from irregularly sampled data}, journal = {Ultrasound in medicine \& biology}, volume = {29}, number = {2}, year = {2003}, pages = {255{\textendash}269}, publisher = {Elsevier}, author = {Raul San Jose-Estepar and Marcos Martin-Fernandez and Caballero-Mart{\'\i}nez, P Pablo and Carlos Alberola-Lopez and Juan Ruiz-Alzola} } @article {aja2002fuzzy, title = {A fuzzy MHT algorithm applied to text-based information tracking}, journal = {Fuzzy Systems, IEEE Transactions on}, volume = {10}, number = {3}, year = {2002}, pages = {360{\textendash}374}, publisher = {IEEE}, author = {Santiago Aja-Fern{\'a}ndez and Carlos Alberola-Lopez and Cybenko, George V} } @article {ruiz2000model, title = {Model-based stereo-visual tracking: Covariance analysis and tracking schemes}, journal = {Signal Processing}, volume = {80}, number = {1}, year = {2000}, pages = {23{\textendash}43}, publisher = {Elsevier}, author = {Juan Ruiz-Alzola and Carlos Alberola-Lopez and Corredera, Jose-Ram{\'o}n Casar} } @inbook {alberola2000disnei, title = {disnei: A collaborative environment for medical images analysis and visualization}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2000}, year = {2000}, publisher = {Springer}, organization = {Springer}, author = {Carlos Alberola-Lopez and Rub{\'e}n C{\'a}rdenes-Almeida and Marcos Martin-Fernandez and Miguel Angel Martin-Fernandez and Rodr{\'\i}guez-Florido, Miguel and Juan Ruiz-Alzola} } @article {409, title = {Cost functions to estimate a posteriori probabilities in multiclass problems}, journal = {IEEE Transactions on Neural Networks}, volume = {10}, year = {1999}, pages = {645-656}, abstract = {

The problem of designing cost functions to estimate a posteriori probabilities in multiclass problems is addressed in this paper. We establish necessary and sufficient conditions that these costs must satisfy in one-class one-output networks whose outputs are consistent with probability laws. We focus our attention on a particular subset of the corresponding cost functions; those which verify two usually interesting properties: symmetry and separability (well-known cost functions, such as the quadratic cost or the cross entropy are particular cases in this subset). Finally, we present a universal stochastic gradient learning rule for single-layer networks, in the sense of minimizing a general version of these cost functions for a wide family of nonlinear activation functions.

}, keywords = {Cost functions, Estimation, Functions, Learning algorithms, Multiclass problems, Neural networks, Pattern recognition, Probability, Problem solving, Random processes, Stochastic gradient learning rule}, issn = {10459227}, doi = {10.1109/72.761724}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0032643080\&partnerID=40\&md5=d528195bd6ec84531e59ddd2ececcd46}, author = {Jes{\'u}s Cid-Sueiro and J I Arribas and S Urban-Munoz and A R Figueiras-Vidal} } @conference {412, title = {Estimates of constrained multi-class a posteriori probabilities in time series problems with neural networks}, booktitle = {Proceedings of the International Joint Conference on Neural Networks}, year = {1999}, publisher = {IEEE, United States}, organization = {IEEE, United States}, address = {Washington, DC, USA}, abstract = {

In time series problems, where time ordering is a crucial issue, the use of Partial Likelihood Estimation (PLE) represents a specially suitable method for the estimation of parameters in the model. We propose a new general supervised neural network algorithm, Joint Network and Data Density Estimation (JNDDE), that employs PLE to approximate conditional probability density functions for multi-class classification problems. The logistic regression analysis is generalized to multiple class problems with softmax regression neural network used to model the a-posteriori probabilities such that they are approximated by the network outputs. Constraints to the network architecture, as well as to the model of data, are imposed, resulting in both a flexible network architecture and distribution modeling. We consider application of JNDDE to channel equalization and present simulation results.

}, keywords = {Approximation theory, Computer simulation, Constraint theory, Data structures, Joint network-data density estimation (JNDDE), Mathematical models, Multi-class a posteriori probabilities, Neural networks, Partial likelihood estimation (PLE), Probability density function, Regression analysis}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0033325263\&partnerID=40\&md5=8c6134020b0b2a9c5ab05b131c070b88}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and T Adali and H Ni and B Wang and A R Figueiras-Vidal} } @conference {411, title = {Neural architectures for parametric estimation of a posteriori probabilities by constrained conditional density functions}, booktitle = {Neural Networks for Signal Processing - Proceedings of the IEEE Workshop}, year = {1999}, publisher = {IEEE, Piscataway, NJ, United States}, organization = {IEEE, Piscataway, NJ, United States}, address = {Madison, WI, USA}, abstract = {

A new approach to the estimation of {\textquoteright}a posteriori{\textquoteright} class probabilities using neural networks, the Joint Network and Data Density Estimation (JNDDE), is presented in this paper. It is based on the estimation of the conditional data density functions, with some restrictions imposed by the classifier structure; the Bayes{\textquoteright} rule is used to obtain the {\textquoteright}a posteriori{\textquoteright} probabilities from these densities. The proposed method is applied to three different network structures: the logistic perceptron (for the binary case), the softmax perceptron (for multi-class problems) and a generalized softmax perceptron (that can be used to map arbitrarily complex probability functions). Gaussian mixture models are used for the conditional densities. The method has the advantage of establishing a distinction between the network parameters and the model parameters. Complexity on any of them can be fixed as desired. Maximum Likelihood gradient-based rules for the estimation of the parameters can be obtained. It is shown that JNDDE exhibits a more robust convergence characteristics than other methods of a posteriori probability estimation, such as those based on the minimization of a Strict Sense Bayesian (SSB) cost function.

}, keywords = {Asymptotic stability, Constraint theory, Data structures, Gaussian mixture models, Joint network and data density estimation, Mathematical models, Maximum likelihood estimation, Neural networks, Probability}, doi = {https://doi.org/10.1109/NNSP.1999.788145}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0033321049\&partnerID=40\&md5=7967fa377810cc0c3e6a4d9020024b80}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and T Adali and A R Figueiras-Vidal} } @conference {410, title = {Neural networks to estimate ML multi-class constrained conditional probability density functions}, booktitle = {Proceedings of the International Joint Conference on Neural Networks}, year = {1999}, publisher = {IEEE, United States}, organization = {IEEE, United States}, address = {Washington, DC, USA}, abstract = {

In this paper, a new algorithm, the Joint Network and Data Density Estimation (JNDDE), is proposed to estimate the {\textquoteleft}a posteriori{\textquoteright} probabilities of the targets with neural networks in multiple classes problems. It is based on the estimation of conditional density functions for each class with some restrictions or constraints imposed by the classifier structure and the use Bayes rule to force the a posteriori probabilities at the output of the network, known here as a implicit set. The method is applied to train perceptrons by means of Gaussian mixture inputs, as a particular example for the Generalized Softmax Perceptron (GSP) network. The method has the advantage of providing a clear distinction between the network architecture and the model of the data constraints, giving network parameters or weights on one side and data over parameters on the other. MLE stochastic gradient based rules are obtained for JNDDE. This algorithm can be applied to hybrid labeled and unlabeled learning in a natural fashion.

}, keywords = {Generalized softmax perceptron (GSP) network, Joint network and data density estimation (JNDDE), Mathematical models, Maximum likelihood estimation, Neural networks, Probability density function, Random processes}, doi = {https://doi.org/10.1109/IJCNN.1999.831174}, url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0033326060\&partnerID=40\&md5=bb38c144dac0872f3a467dc12170e6b6}, author = {J I Arribas and Jes{\'u}s Cid-Sueiro and T Adali and A R Figueiras-Vidal} } @article {alberola1999object, title = {Object CFAR detection in gamma-distributed textured-background images}, journal = {IEE Proceedings-Vision, Image and Signal Processing}, volume = {146}, number = {3}, year = {1999}, pages = {130{\textendash}136}, publisher = {IEE}, author = {Carlos Alberola-Lopez and JR Casar-Corredera and de Miguel-Vela, G} } @conference {450, title = {A Comparison of CFAR Strategies for Blob Detection in Textured Images}, booktitle = {European Signal Processing Conference (EUSIPCO), 1996}, year = {1996}, publisher = {Elsevier}, organization = {Elsevier}, author = {Carlos Alberola-Lopez and Casar-Corredera, Jos{\'e} Ramon and Juan Ruiz-Alzola} } @proceedings {alberola1996region, title = {A Region Oriented CFAR Approach to the Detection of Extensive Targets in Textured Images}, year = {1996}, pages = {195}, publisher = {Elsevier Science Ltd}, author = {Carlos Alberola-Lopez and Casar-Corredera, Jos{\'e} Ramon and Juan Ruiz-Alzola} }