You are all cordially invited to the AMLab Seminar on Thursday 5th November at 4:00 p.m CET on Zoom, where Tim Bakker will give a talk titled ” Experimental design for MRI by greedy policy search “.
Title: Experimental design for MRI by greedy policy search
Abstract: In today’s clinical practice, magnetic resonance imaging (MRI) is routinely accelerated through subsampling of the associated Fourier domain. Currently, the construction of these subsampling strategies – known as experimental design – relies primarily on heuristics. We propose to learn experimental design strategies for accelerated MRI with policy gradient methods. Unexpectedly, our experiments show that a simple greedy approximation of the objective leads to solutions nearly on-par with the more general non-greedy approach. We offer a partial explanation for this phenomenon rooted in greater variance in the non-greedy objective’s gradient estimates, and experimentally verify that this variance hampers non-greedy models in adapting their policies to individual MR images. We empirically show that this adaptivity is key to improving subsampling designs.
Paper Link: https://arxiv.org/pdf/2010.16262.pdf
To gain more deep insights into MRI research using Reinforcement Learning, feel free to join and discuss it! See you there 🙂 !