@article {997, title = {Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning}, journal = {Medical Image Analysis}, volume = {94}, year = {2024}, pages = {103134}, abstract = {

Diffusion-relaxation MRI aims to extract quantitative measures that characterise microstructural tissue properties such as orientation, size, and shape, but long acquisition times are typically required. This work proposes a physics-informed learning framework to extract an optimal subset of diffusion-relaxation MRI measurements for enabling shorter acquisition times, predict non-measured signals, and estimate quantitative parameters. In vivo and synthetic brain 5D-Diffusion-T1-T2*-weighted MRI data obtained from five healthy subjects were used for training and validation, and from a sixth participant for testing. One fully data-driven and two physics-informed machine learning methods were implemented and compared to two manual selection procedures and Cram{\'e}r–Rao lower bound optimisation. The physics-informed approaches could identify measurement-subsets that yielded more consistently accurate parameter estimates in simulations than other approaches, with similar signal prediction error. Five-fold shorter protocols yielded error distributions of estimated quantitative parameters with very small effect sizes compared to estimates from the full protocol. Selected subsets commonly included a denser sampling of the shortest and longest inversion time, lowest echo time, and high b-value. The proposed framework combining machine learning and MRI physics offers a promising approach to develop shorter imaging protocols without compromising the quality of parameter estimates and signal predictions.

}, keywords = {Brain, Diffusion-relaxation, Quantitative MRI, machine learning}, issn = {1361-8415}, doi = {https://doi.org/10.1016/j.media.2024.103134}, url = {https://www.sciencedirect.com/science/article/pii/S1361841524000598}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Maxime Descoteaux and Hugo Larochelle and Jana Hutter and Derek K. Jones and Chantal M.W. Tax} } @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 {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 {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 {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} } @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 {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 {843, title = {Identificacion of MRI-based psychosis subtypes: Replication and refinement}, journal = {Progress in Neuro-Psychopharmacology and Biological Psychiatry}, volume = {100}, year = {2020}, pages = {109907}, abstract = {

The identification of the cerebral substrates of psychoses such as schizophrenia and bipolar disorder is likely hampered by its biological heterogeneity, which may contribute to the low replication of results in the field. In this study we aimed to replicate in a completely new sample and supplement the results of a previous study with additional data on this topic. In the aforementioned study we identified a schizophrenia cluster characterized by high mean cortical curvature and low cortical thickness, subcortical hypometabolism and progressive negative symptoms. Here, we have used magnetic resonance images from 61 schizophrenia and 28 bipolar patients, as well as 51 healthy controls and a cluster analysis to search for possible subgroups primarily characterized by cerebral structural data. Diffusion tensor imaging (fractional anisotropy, FA), cognition, clinical data and electroencephalographic (EEG) modulation during a P300 task were used to validate the possible clusters. Two clusters of patients were identified. The first cluster (29 schizophrenia and 18 bipolar patients) showed decreased cortical thickness and area values, as well as lower subcortical volumes and higher cortical curvature in some regions, as compared to the second cluster. This first cluster also showed decreased FA in frontal lobe connections and worse cognitive performance. Although this cluster also showed longer illness duration, there were first episode patients in both clusters and treatment doses and types were not different between clusters. Both clusters of patients showed decreased EEG task-related modulation. In conclusion, our data give additional support to a distinct biologically based cluster encompassing schizophrenia and bipolar disorder patients with cortical and subcortical alterations, hampered cortical connectivity and lower cognitive performance.

}, keywords = {Biotypes, Cortical thickness, Curvature, Subtypes, bipolar disorder, schizophrenia}, issn = {0278-5846}, doi = {https://doi.org/10.1016/j.pnpbp.2020.109907}, url = {http://www.sciencedirect.com/science/article/pii/S0278584619309595}, author = {{\'A}lvaro Planchuelo-G{\'o}mez and Lubeiro, Alba and N{\'u}{\~n}ez-Novo, Pablo and Gomez-Pilar, Javier and Rodrigo de Luis-Garc{\'\i}a and del Valle, Pilar and Mart{\'\i}n-Santiago, {\'O}scar and P{\'e}rez-Escudero, Adela and Vicente Molina} } @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 {888, title = {Phenotypic characterization of acute headache attributed to SARS-CoV-2: An ICHD-3 validation study on 106 hospitalized patients}, journal = {Cephalalgia}, volume = {40}, year = {2020}, month = {2020}, pages = {1432-1442}, abstract = {Introduction: Headache is a common symptom of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In this study, we aimed to characterize the phenotype of headache attributed to SARS-CoV-2 infection and to test the International Classification of Headache Disorders (ICHD-3) phenotypic criteria for migraine and tension-type headache. Methods: The study design was a cross-sectional study nested in a cohort. We screened all consecutive patients that were hospitalized and had a positive SARS-CoV-2 test. We included patients that described headache if the headache was not better explained by another ICHD-3 diagnosis. Patients were interviewed by two neurologists. Results: We screened 580 patients and included 130 (mean age 56 years, 64\% female). Headache was the first symptom of the infection in 26\% of patients and appeared within 24 hours in 62\% of patients. The headache was bilateral in 85\%, frontal in 83\%, and with pressing quality in 75\% of patients. Mean intensity was 7.1, being severe in 64\%. Hypersensitivity to stimuli occurred in 57\% of patients. ICHD-3 criteria for headache attributed to systemic viral infection were fulfilled by 94\% of patients; phenotypic criteria for migraine were fulfilled by 25\% of patients, and tension-type headache criteria by 54\% of patients. Conclusion: Headache attributed to SARS-CoV-2 infection in hospitalized patients has severe intensity, frontal predominance and oppressive quality. It occurs early in the course of the disease. Most patients fulfilled ICHD-3 criteria for headache attributed to systemic viral infection; however, the phenotype might resemble migraine in a quarter of cases and tension-type headache in half of the patients.}, issn = {0333-1024}, doi = {10.1177/0333102420965146}, url = {https://doi.org/10.1177/0333102420965146}, author = {Trigo L{\'o}pez, Javier and Garc{\'\i}a-Azor{\'\i}n, David and {\'A}lvaro Planchuelo-G{\'o}mez and Garc{\'\i}a-Iglesias, Cristina and Due{\~n}as-Guti{\'e}rrez, Carlos and {\'A}ngel L. Guerrero} } @inbook {818, title = {Return-to-Axis Probability Calculation from Single-Shell Acquisitions}, booktitle = {Computational Diffusion MRI}, year = {2019}, pages = {29-41}, publisher = {Springer}, organization = {Springer}, isbn = {978-3-030-05830-2}, doi = {10.1007/978-3-030-05831-9_3}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Molendowska, Malwina and Tomasz Pieciak and Luis-Garc{\'\i}a, Rodrigo} } @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 {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 {761, title = {Topography of activation deficits in schizophrenia during P300 task related to cognition and structural connectivity}, journal = {European Archives of Psychiatry and Clinical Neuroscience}, year = {2018}, month = {Feb}, issn = {1433-8491}, doi = {10.1007/s00406-018-0877-3}, url = {https://doi.org/10.1007/s00406-018-0877-3}, author = {Vicente Molina and Bachiller, Alejandro and Rodrigo de Luis-Garc{\'\i}a and Lubeiro, Alba and Poza, Jes{\'u}s and Hornero, Roberto and Alonso, Joan Francesc and Ma{\~n}anas, Miguel Angel and Marqu{\'e}s, Patricia and Romero, Sergio} } @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 {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.} } @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} } @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} } @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} } @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 {476, title = {Localized abnormalities in the cingulum bundle in patients with schizophrenia: A Diffusion Tensor tractography study}, journal = {NeuroImage: Clinical}, volume = {5}, year = {2014}, pages = {93{\textendash}99}, abstract = {

The cingulum bundle (CB) connects gray matter structures of the limbic system and as such has been implicated in the etiology of schizophrenia. There is growing evidence to suggest that the CB is actually comprised of a conglomeration of discrete sub-connections. The present study aimed to use Diffusion Tensor tractography to subdivide the CB into its constituent sub-connections, and to investigate the structural integrity of these sub-connections in patients with schizophrenia and matched healthy controls. Diffusion Tensor Imaging scans were acquired from 24 patients diagnosed with chronic schizophrenia and 26 matched healthy controls. Deterministic tractography was used in conjunction with FreeSurfer-based regions-of-interest to subdivide the CB into 5 sub-connections (I1 to I5). The patients with schizophrenia exhibited subnormal levels of FA in two cingulum sub-connections, specifically the fibers connecting the rostral and caudal anterior cingulate gyrus (I1) and the fibers connecting the isthmus of the cingulate with the parahippocampal cortex (I4). Furthermore, while FA in the I1 sub-connection was correlated with the severity of patients{\textquoteright} positive symptoms (specifically hallucinations and delusions), FA in the I4 sub-connection was correlated with the severity of patients{\textquoteright} negative symptoms (specifically affective flattening and anhedonia/asociality). These results support the notion that the CB is a conglomeration of structurally interconnected yet functionally distinct sub-connections, of which only a subset are abnormal in patients with schizophrenia. Furthermore, while acknowledging the fact that the present study only investigated the CB, these results suggest that the positive and negative symptoms of schizophrenia may have distinct neurobiological underpinnings.

}, author = {Whitford, Thomas J and Lee, Sun Woo and Oh, Jungsu S and Rodrigo de Luis-Garc{\'\i}a and Savadjiev, Peter and Alvarado, Jorge L and Carl-Fredik Westin and Niznikiewicz, Margaret and Nestor, Paul G and McCarley, Robert W} } @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 {436, title = {Comparativa entre distribuciones alpha-estables para modelar tasas de transferencia obtenidas a partir de registros de SNMP y NetFlow}, booktitle = {Jornadas de Ingenier{\'\i}a Telem{\'a}tica (JITEL)}, year = {2013}, publisher = {Asociaci{\'o}n de Telem{\'a}tica (ATEL)}, organization = {Asociaci{\'o}n de Telem{\'a}tica (ATEL)}, address = {Granada, Spain}, author = {Stoppa, Matteo and L{\'o}pez-de-Vergara-M{\'e}ndez, Jorge E. and Federico Simmross-Wattenberg and Garc{\'\i}a-Dorado, Jos{\'e} Luis} } @article {brion2013noise, title = {Noise correction for HARDI and HYDI data obtained with multi-channel coils and Sum of Squares reconstruction: An anisotropic extension of the LMMSE}, journal = {Magnetic resonance imaging}, volume = {31}, number = {8}, year = {2013}, pages = {1360{\textendash}1371}, publisher = {Elsevier}, author = {V{\'e}ronique Brion and Poupon, Cyril and Riff, Olivier and Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Mangin, Jean-Fran{\c c}ois and Le Bihan, Denis and Poupon, Fabrice} } @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} } @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} } @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} } @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} } @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 {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} } @inbook {brion2011parallel, title = {Parallel MRI noise correction: an extension of the LMMSE to non central $\chi$ distributions}, booktitle = {Medical Image Computing and Computer-Assisted Intervention{\textendash}MICCAI 2011}, year = {2011}, pages = {226{\textendash}233}, publisher = {Springer Berlin Heidelberg}, organization = {Springer Berlin Heidelberg}, author = {V{\'e}ronique Brion and Poupon, Cyril and Riff, Olivier and Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Mangin, Jean-Fran{\c c}ois and Le Bihan, Denis and Poupon, Fabrice} } @article {garmendia2009acute, title = {Acute myocardial infarction circadian rhythm in a geriatric population in Castilla y Leon}, journal = {Journal of the American Geriatrics Society}, volume = {57}, number = {7}, year = {2009}, pages = {1312{\textendash}1313}, publisher = {Wiley Online Library}, author = {Jose Ramon Garmendia-Leiza and Jesus Maria Andres-de-Llano and Julio Ardura-Fernández and Juan Bautista Lopez-Messa and MD Aguilar-Garcia and Carlos Alberola-Lopez} } @conference {478, title = {Automatic segmentation of white matter structures from DTI using tensor invariants and tensor orientation}, booktitle = {Proc. Intl. Soc. Mag. Reson. Med}, year = {2009}, author = {Rodrigo de Luis-Garc{\'\i}a and Lopez, C Alberola and Kindlmann, G and Carl-Fredik Westin} } @book {aja2009tensors, title = {Tensors in image processing and computer vision}, year = {2009}, publisher = {Springer}, organization = {Springer}, author = {Santiago Aja-Fern{\'a}ndez and Rodrigo de Luis-Garc{\'\i}a and Tao, Dacheng and Li, Xuelong} } @article {lopez2005age, title = {Age as modifying factor of circadian rhythm of acute myocardial infarction}, journal = {MEDICINA INTENSIVA}, volume = {29}, number = {9}, year = {2005}, pages = {455}, publisher = {IDEPSA}, author = {Juan Bautista Lopez-Messa and JR Garmendia-Leiza and MD Aguilar-Garcia and Jes{\'u}s Mar{\'\i}a And De Llano and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @article {lopez2005edad, title = {La edad como factor modificador del ritmo circadiano del infarto agudo de miocardio}, journal = {Medicina intensiva}, volume = {29}, number = {9}, year = {2005}, pages = {455{\textendash}461}, publisher = {Elsevier}, author = {Juan Bautista Lopez-Messa and JR Garmendia-Leiza and MD Aguilar-Garcia and Jes{\'u}s Mar{\'\i}a And De Llano and Julio Ardura-Fernández and Carlos Alberola-Lopez} } @article {lopez2004cardiovascular, title = {Cardiovascular risk factors in the circadian rhythm of acute myocardial infarction}, journal = {Revista Espa{\~n}ola de Cardiolog{\'\i}a (English Edition)}, volume = {57}, number = {9}, year = {2004}, pages = {850{\textendash}858}, publisher = {Elsevier}, author = {L{\'o}pez Messa, Juan B and JR Garmendia-Leiza and Aguilar Garc{\'\i}a, Mar{\'\i}a D and Jes{\'u}s Mar{\'\i}a And De Llano and Alberola L{\'o}pez, Carlos and Fern{\'a}ndez, Julio Ardura} } @article {garmendia2004diferencias, title = {Diferencias en el ritmo circadiano del infarto de miocardio seg{\'u}n su extensi{\'o}n electrocardiogr{\'a}fica}, journal = {Medicina clinica}, volume = {123}, number = {17}, year = {2004}, pages = {641{\textendash}645}, publisher = {Elsevier Doyma}, author = {Jose Ramon Garmendia-Leiza and Juan Bautista Lopez-Messa and Jesus Maria Andres-de-Llano and Carlos Alberola-Lopez and Julio Ardura-Fernández} } @article {garmendia2004differential, title = {Differential circadian rhythms in myocardial infarction according to its extent by electrocardiogram}, journal = {Medicina clinica}, volume = {123}, number = {17}, year = {2004}, pages = {641{\textendash}646}, author = {Jose Ramon Garmendia-Leiza and Juan Bautista Lopez-Messa and Jesus Maria Andres-de-Llano and Carlos Alberola-Lopez and Julio Ardura-Fernández} } @article {lopez2004factores, title = {Factores de riesgo cardiovascular en el ritmo circadiano del infarto agudo de miocardio}, journal = {Revista Espa{\~n}ola de Cardiolog{\'\i}a (English Edition)}, volume = {57}, number = {9}, year = {2004}, pages = {850{\textendash}858}, publisher = {Elsevier}, author = {L{\'o}pez Messa, Juan B and JR Garmendia-Leiza and Aguilar Garc{\'\i}a, Mar{\'\i}a D and Jes{\'u}s Mar{\'\i}a And De Llano and Alberola L{\'o}pez, Carlos and Ardura Fern{\'a}ndez, Julio} } @proceedings {de2002neural, title = {A neural architecture for bone age assessment}, year = {2002}, pages = {161{\textendash}166}, author = {Rodrigo de Luis-Garc{\'\i}a and J I Arribas and Santiago Aja-Fern{\'a}ndez and Lopez, C Alberola} } @proceedings {hornero1997dsp, title = {A DSP Implementation of Wavelet Transform to Detect Epileptiform Activity in the EEG}, year = {1997}, pages = {692{\textendash}696}, author = {Hornero, R and Marcos Martin-Fernandez and Alonso, A and Izquierdo, A and Lopez, M} }