Radiation design in computed tomography via convex optimization

Proper X-ray radiation design (via dynamic fluence field modulation, FFM) allows reducing effective radiation dose in computed tomography without compromising image quality. It takes into account patient anatomy, radiation sensitivity of different organs and tissues, and location of regions of interest. We account for all these factors within a general convex optimization framework.

Short bio:

Michael Zibulevsky received his BS-MS in Electrical Engineering from MIIT – Moscow Institute of Transportation Engineering,  and PhD in Operations Research from the Technion – Israel Institute of Technology. He is currently with the Dept. of Computer Science at the Technion. Michael Zibulevsky is one of the founders of Sparse Component Analysis. His research interests include numerical methods of optimization, sparse signal representations, deep neural networks and their applications in signal/image processing and inverse problems.

Joint work with Anatoli Juditsky and  Arkadi Nemirovski.