MRF
Speaker: Ramin Zabih , Associate Professor, Cornell University
Date: November 10 2006
Time: 3:30PM to 4:30PM
Location: Seminar Room D463 (Star)
Host: Gerald Dalley, MIT CSAIL
Contact: C. Mario Christoudias, Gerald Dalley, 3-4278, 3-6095, cmch@csail.mit.edu, dalleyg@mit.edu
Relevant URL: Markov Random Fields (MRF's) are a very effective way to impose spatial
smoothness in computer vision. I will describe an application of MRF's to a
non-traditional but important problem in medical imaging: the reconstruction
of MR images from raw fourier data. This can be formulated as a linear
inverse problem, where the goal is to find a spatially smooth solution while
permitting discontinuities. Although it is easy to apply MRF's for MR
reconstruction, the resulting energy minimization problem poses some
interesting challenges. It lies outside of the class of energy functions that
can be straightforwardly minimized with graph cuts. I will show how a 1984
construction due to Hammer and coauthors allows graph cuts to be adapted to
solve this problem, and will demonstrate some preliminary results that are
extremely promising.
Joint work with Ashish Raj and Gurmeet Singh.
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