Advanced Processing of MRI and PET Images: New Quantitative Approaches to Study Long COVID, Brain Health, and Sarcopenia
Dr Martin A. Belzunce.
Faculty Researcher at CONICET / Associate Professor at UNSAM. Laboratorio de Procesamiento de Imágenes Médicas (LAPIM). Instituto de Ciencias Físicas (ICIFI) UNSAM-CONICET, Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín (UNSAM), Buenos Aires (Argentina)
Theatre room, CiMUS
About
This talk will present recent research combining MRI and PET imaging with advanced computational methods to study long COVID, brain aging, and sarcopenia. First, we will show the impact of long COVID on the brain using MRI and PET data from a dedicated cohort studied in Argentina. Then, we will briefly explore quantitative AI-based biomarkers, including brain age prediction from structural MRI, Alzheimer’s classification from fMRI, and intramuscular fat quantification from quantitative MRI
Bio
Martín Belzunce is a CONICET researcher and faculty member at UNSAM (Argentina), with a background in electronic engineering and a PhD in image processing. He previously held research positions at King’s College London and the UK NHS. His work focuses on medical image processing and analysis for the development of imaging biomarkers of aging, neurodegeneration, and sarcopenia.
Hosted by Pablo Aguiar, PI Molecular Imaging Biomarkers and Theragnosis Lab, CiMUS
Certificates of attendance will be provided upon request at cimus.xestion [at] usc.es (cimus[dot]xestion[at]usc[dot]es). Please do not forget to enter your name and surname in the printout given during the lecture.