Prof. Daniel Topgaard
Lund University, Sweden

Keynote Speech
Prof. Daniel Topgaard
Title: Enhancing diffusion MRI using AI

Abstract:
Diffusion MRI provides information about micrometer-scale structures in the living human brain in apparent contradiction of the millimeter-scale pixel dimensions of the actually recorded images. Despite a large body of literature demonstrating its utility in both research and clinical practice, the method faces numerous challenges that in principle could be overcome with AI. These challenges include excessive time requirements for data acquistion or processing, difficulties in correlating imaging metrics with disease states, and the ill-posedness of translating the imaging results to more fundamental and understandable microstructural properties such as cell densities, sizes, shapes, orientations, and membrane permeabilities. Building on many years of applying basic knowledge from physics and chemistry to increase the information content of the acquired data, this talk will give an overview of our recent and on-going work in using AI to enhance diffusion MRI in the aspects of signal processing, disease state classification, and microstructural interpretation.

Biography:
Daniel Topgaard is a Professor of Physical Chemistry at Lund University, Sweden. Following a Ph.D. degree in Lund 2003 he was a postdoctoral fellow with Alex Pines at UC Berkeley developing NMR spectroscopy for inhomogeneous fields. His current research is focused on solid-state NMR and diffusion MRI methods for investigating structure and dynamics of soft matter systems from lipid membranes to the living human brain. He is a member of the Scientific Council for Natural and Engineering Sciences at the Swedish Research Council, the Board of Trustees of the European Magnetic Resonance (EUROMAR) conference, the Executive Committee of the Experimental NMR Conference (ENC), and the Executive Editorial Board of the Magnetic Resonance journal. He is an Honorary Professor at the Zhongnan Hospital of Wuhan University and Visiting Professor at Beijing University of Posts and Telecommunications.