Brain image analysis across scales: from high-resolution histology to low-resolution clinical and portable MRI

In this talk, I will summarize work done at my group over the last decade, on brain image analysis of brain MRI. I will start with our initial efforts on high-resolution atlasing using ex vivo MRI and histology, with an emphasis on our recently released NextBrain, which is the first probabilistic atlas of the whole human brain built with high-resolution 3D histology, and which can be used to automatically segment MRI scans (in vivo or ex vivo) into 300+ regions of interest. Then I will move on to our family of deep convolutional neural networks trained on synthetic, domain-randomized data. These networks can, for the first time, segment MRI scans of any orientation, resolution, and contrast “out of the box”, without retraining. I will show applications to large-scale analysis of clinical scans, models of pathology, analysis of low-field scans acquired with a portable device, and foundation models. 

Juan Eugenio Iglesias is Associate Professor of Radiology at the Martinos Center for Biomedical Imaging (Massachusetts General Hospital and Harvard Medical School), where he directs the Laboratory for Ex Vivo Modeling of Neuroanatomy (LEMoN) and co-directs the Center for Machine Learning with Dr. Matt Rosen. Dr. Iglesias also has affiliate appointments at University College London (UCL) and the Massachusetts Institute of Technology (MIT). His research lies at the intersection of artificial intelligence and neuroimaging. His work has enabled the analysis of brain MRI data at a superior level of detail, as well as the application of research neuroimaging methods to scans with low in-plane resolution – including clinical and portable MRI scans. Dr. Iglesias holds MSc degrees in Electrical and Telecommunication Engineering from the Royal Institute of Technology (KTH, Stockholm, Sweden) and the University of Seville, respectively. He completed his PhD in Biomedical Engineering at the University of California, Los Angeles (UCLA) in 2011. He is the recipient of a Fulbright Science of Technology Award, a Marie Curie fellowship, a Starting Grant of the European Research Council, and several NIH grants.