EE Seminar: Applications of Subspace and Low-Rank Methods for Dynamic and Multi-Contrast Magnetic Resonance Imaging
(The talk will be given in English)
Speaker: Prof. Michael Lustig
EE & CS, University of California, Berkeley
Monday, November 28th, 2016
15:00 - 16:00
Room 011, Kitot Bldg., Faculty of Engineering
Applications of Subspace and Low-Rank Methods for Dynamic and Multi-Contrast Magnetic Resonance Imaging
Abstract
There has been much work in recent years to develop methods for recovering signals from insufficient data. One very successful direction of developments are subspace methods that constrain data to live in a lower dimensional space. These approaches are motivated by theoretical results in recovering incomplete low-rank matrices as well as exploiting the natural redundancy of multidimensional signals. In this talk I will present our research group’s contributions in this area. I will start with describing a new decomposition that can represent dynamic images as a sum of multi-scale low-rank matrices, which can very efficiently capture spatial and temporal correlations in multiple scales and dimensions. I will then describe and show results from applications using subspace and low-rank methods for highly accelerated multi-contrast Magnetic Resonance Imaging (MRI) and for the purpose of motion correction in MRI.
