Deformation-invariant sparse coding
Name
818354481-MIT.pdf
Description
Full printable version
Size
7 MB
Format
Adobe PDF
Checksum (MD5)
621c2ae85ccf1a74c1a1b8cff7037a0b
Author(s)
Chen, George H
Advisor(s)
Polina Golland.
Date Issued
2012
Publisher
Massachusetts Institute of Technology
Abstract
Sparse coding represents input signals each as a sparse linear combination of a set of basis or dictionary elements where sparsity encourages representing each input signal with a few of the most indicative dictionary elements. In this thesis, we extend sparse coding to allow dictionary elements to undergo deformations, resulting in a general probabilistic model and accompanying inference algorithm for estimating sparse linear combination weights, dictionary elements, and deformations. We apply our proposed method on functional magnetic resonance imaging (fMRI) data, where the locations of functional regions in the brain evoked by a specific cognitive task may vary across individuals relative to anatomy. For a language fMRI study, our method identifies activation regions that agree with known literature on language processing. Furthermore, the deformations learned by our inference algorithm produce more robust group-level effects than anatomical alignment alone.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 87-91).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
M.I.T. theses are protected by
copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
permission. See provided URL for inquiries about permission.
copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
permission. See provided URL for inquiries about permission.
Persistent DSpace Link
