Or Perlman, Ph.D.
Senior Lecturer, Department of Biomedical Engineering
Tel Aviv University
Speech Title:
AI Boosted Molecular MRI
Abstract:
In this talk, a novel imaging approach for rapid and quantitative molecular magnetic resonance imaging (MRI) will be presented. It combines a model depicting the effects of various metabolites and proteins on the MR signal during non-steady-state acquisition with artificial intelligence (AI)-based image reconstruction. The usefulness of this strategy for generating quantitative biomarker maps of protein and lipid concentrations and intracellular pH will be demonstrated using a rodent brain-tumor model, where applying the method allowed for the early detection of apoptotic response to virus-based cancer therapy. Next, translational studies will be described, where reproducible and quantitative 3D molecular maps of the entire normal human brain were obtained across three different hospitals. Finally, a machine-learning-based framework for the automatic invention of quantitative molecular imaging acquisition protocols will be presented, and future research directions will be outlined.
Bio:
Dr. Or Perlman is a Senior Lecturer at the Department of Biomedical Engineering and Sagol School of Neuroscience, Tel Aviv University (TAU), Israel. He received his BSc (Cum Laude) and MSc (Cum Laude) from Ben-Gurion University and his Ph.D. from the Technion, Israel, all in the field of Biomedical Engineering. Before TAU, he was a Postdoctoral Research Fellow at the Department of Radiology, Harvard Medical School and Massachusetts General Hospital, funded by the European Union’s Marie Sklodowska-Curie Global Fellowship. His lab develops MRI and machine intelligence strategies to explore the molecular mechanisms underlying brain disease and develop methods for early diagnosis and therapy optimization.
