Title: Generalizable and democratic AI: from classical techniques to modern neural networks


Every year, millions of brain MRI scans are acquired in hospitals, which is a figure considerably larger than the size of any research dataset. Therefore, the ability to analyze such scans could transform neuroimaging research – particularly for underrepresented populations that research-oriented datasets like ADNI or UK BioBank often neglect. However, the potential of these scans remains untapped since no automated algorithm is robust enough to cope with the high variability in clinical acquisitions (MR contrasts, resolutions, orientations, artifacts, and subject populations). In this talk, I will present techniques developed by our group over the last few years that enable robust analysis of heterogeneous clinical datasets “in the wild”, including segmentation, registration, super-resolution, and synthesis. The talk will cover both: (i) classical Bayesian techniques, based on high-resolution atlases derived from ex vivo MRI and histology, and (ii) modern neural networks, relying on domain randomization methods for enhanced generalizability. I will present results on thousands of brain scans from our hospital with highly heterogeneous orientation, resolution, and contrast, as well as results on low-field scans acquired with a portable scanner.


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.


Date: 22nd March 2024

Time: (16:00 UTC), (17:00 WAT), (12:00 EDT), (11:00 CDT)

Meeting Link: To be sent to only registered participants


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