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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.
