Lucilio Cordero-Grande

Also published under:L. Cordero-Grande, Lucilio Cordero Grande

Affiliation

Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain,
CIBER-BBN, ISCIII, Madrid, Spain
Department, School of Biomedical Engineering and Imaging Sciences, Centre for the Developing Brain and Biomedical Engineering, King’s College London, King’s Health Partners, St Thomas’ Hospital, London, U.K

Topic

Magnetic Resonance Imaging,Motion Correction,Age Prediction,Angular Domain,Artifacts In Data,B0 Field,B1 Field,Biomechanical Model,Brain Connectivity,Brain Microstructure,Brain Regions Of Interest,Breast Cancer,Breast Tumors,Breast Volume,Breast-conserving Surgery,Cancer In Women Worldwide,Computed Tomography Images,Corrupted Data,Diffeomorphic Registration,Diffusion Tensor Imaging,Dispersive Analysis,Distortion Correction,Echo Time,Fetal Body,Fetal Brain,Fetal Imaging,Fetal MRI,Fetal Magnetic Resonance Imaging,Fiber Cross,Fiber Orientation Distribution,Field Distortion,Gaussian Process,Gestational Age Estimation,Gradient Descent,Image Quality,Image Reconstruction,Image Resolution,Intensity Correction,Iterative Gradient Descent,Large Breast,Leave-one-out Cross-validation,Localization Error,Mean Absolute Error,Medial Direction,Motion Compensation,Motion Estimation,Motion Model,Motion Parameters,Motor Level,Noise In Data,

Biography

Lucilio Cordero-Grande received the Ingeniero de Telecomunicacion and Ph.D. degrees from the University of Valladolid, Spain. He was a Research Associate at the Laboratory of Image Processing, Universidad de Valladolid, from 2005 to 2013. He was a Research Fellow at the Centre for the Developing Brain and the Department of Biomedical Engineering, King’s College London, U.K., from 2014 to 2019. Since 2020, he has been a Research Fellow at the Biomedical Image Technologies Laboratory, Universidad Politécnica de Madrid, Madrid. He has coauthored more than 50 articles and 100 conference proceedings. His research interests include applied functional analysis, statistical and variational methods for biomedical image processing, and reconstruction, with a focus on MRI.