Seminar Details
2019-04-30 (14:00) : Data-driven compressed sensing with inexact projected gradient iterations: application to magnetic resonance fingerprinting
At Euler building (room A.002)
Organized by Mathematical Engineering
Speaker :
Mohammad Golbabaee (The University of Bath)
Abstract :
We study the convergence of the iterative projected gradient algorithm where the projection oracles are computed approximately. We apply our results to accelerate solving a class of data driven compressed sensing problems, where we replace iterative exhaustive searches over large data sets by fast approximate nearest neighbour search strategies based on the cover tree data structure.
This talk will also discuss recent advances in rapid quantitative MRI based on the emerging protocol of Magnetic Resonance Fingerprinting (MRF). MRF can be considered as an inverse problem which exploits a particular data driven signal model derived from the MR physics. We discuss the applications of the inexact iterations in addressing the computational challenge of solving such problems.