MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

A stochastic tractography system and applications

Author(s)
Ngo, Tri M. (Tri Minh)
Thumbnail
DownloadFull printable version (8.450Mb)
Other Contributors
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Polina Golland and Carl-Fredrik Westin.
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. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
Neuroscientists hypothesize that the pathologies of some neurological diseases are associated with neuroanatomical abnormalities. Diffusion Tensor Imaging (DTI) and stochastic tractography allow us to investigate white matter architecture non-invasively through measurements of water self diffusion throughout the brain. Many comparative studies of white matter architecture utilize spatially localized comparisons of diffusion characteristics. White matter tractography enables studies of fiber bundle characteristics. Stochastic tractography facilitates these investigations by providing a measure of confidence regarding the inferred fiber bundles. This thesis presents an implementation of an easy to use, open-source stochastic tractography system that will enable novel studies of fiber tract abnormalities. We demonstrate an application of the system on real DTI images and discuss possible studies of frontal lobe fiber differences in Schizophrenia.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
 
Includes bibliographical references (p. 75-77).
 
Date issued
2007
URI
http://hdl.handle.net/1721.1/41652
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.