Title Medical image reconstruction using adaptive signal models

This talk will start with an overview of how machine learning methods
can be used in the context of medical image formation (both acquisition
and reconstruction). Then it will dive deeper into emerging image
reconstruction methods that are based on data-driven signal models, in
contrast with the more mature "hand crafted" mathematical models.
Results from MRI and CT reconstruction will illustrate the ideas.
Jeffrey A. Fessler is the William L. Root Collegiate Professor of EECS.
He is a Professor in the Systems Lab of the ECE Division within the Electrical Engineering and Computer Science department of the College of Engineering, located within the scenic North Campus of The University of Michigan in the terrific town of Ann Arbor, Michigan. He is also affiliated with the Biomedical Engineering Department and with the Division of Nuclear Medicine within the Department of Radiology. My research interests include medical imaging, tomography, nonparametric estimation, and inverse problems, with current and past projects in X-ray CT, MRI, PET, SPECT, radiation therapy, and image registration. I am interested both in developing algorithms for these problems, as well as analyzing and predicting the properties of these algorithms. My students work on a wide variety of imaging projects, both for medical imaging and some non-medical imaging problems.