2026-09-23T16:37:50Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/83482022-01-13T07:53:45Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Van Jay Wedeen and John Belliveau.
Tuch, David Solomon, 1973-
Harvard University--MIT Division of Health Sciences and Technology.
Harvard University--MIT Division of Health Sciences and Technology
2005-08-23T19:22:31Z
2005-08-23T19:22:31Z
2002
2002
http://hdl.handle.net/1721.1/8348
50543782
Thesis (Ph. D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 2002.
Includes bibliographical references.
Magnetic resonance diffusion imaging provides an exquisitely sensitive probe of tissue microstructure. Owing to the microscopic length scale of diffusion in biological tissues, diffusion imaging can reveal histological architecture irresolvable by conventional magnetic resonance imaging methods. However, diffusion imaging methods to date have chiefly been based on analytical models of the underlying diffusion process. For example, diffusion tensor imaging assumes homogeneous Gaussian diffusion within each voxel, an assumption which is clearly invalid for the vast majority of the brain at presently achievable voxel resolutions. In this thesis I developed a diffusion imaging method capable of measuring the microscopic diffusion function within each voxel. In contrast to previous approaches to diffusion imaging, the method presented here does not require any assumptions on the underlying diffusion function. The model-independent approach can resolve complex intravoxel tissue structure including fiber crossing and fiber divergence within a single voxel. The method is capable of resolving not only deep white matter intersections, but also composite tissue structure at the cortical margin, and fiber-specific degeneration in neurodegenerative pathology. In sum, the approach can reveal complex intravoxel tissue structure previously thought to be beyond the scope of diffusion imaging methodology.
by David Solomon Tuch.
Ph.D.
220 p.
19360547 bytes
19360306 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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
Harvard University--MIT Division of Health Sciences and Technology.
Diffusion MRI of complex tissue structure
Diffusion magnetic resonance imaging of complex tissue structure
Thesis
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<Abstract>Magnetic resonance diffusion imaging provides an exquisitely sensitive probe of tissue microstructure. Owing to the microscopic length scale of diffusion in biological tissues, diffusion imaging can reveal histological architecture irresolvable by conventional magnetic resonance imaging methods. However, diffusion imaging methods to date have chiefly been based on analytical models of the underlying diffusion process. For example, diffusion tensor imaging assumes homogeneous Gaussian diffusion within each voxel, an assumption which is clearly invalid for the vast majority of the brain at presently achievable voxel resolutions. In this thesis I developed a diffusion imaging method capable of measuring the microscopic diffusion function within each voxel. In contrast to previous approaches to diffusion imaging, the method presented here does not require any assumptions on the underlying diffusion function. The model-independent approach can resolve complex intravoxel tissue structure including fiber crossing and fiber divergence within a single voxel. The method is capable of resolving not only deep white matter intersections, but also composite tissue structure at the cortical margin, and fiber-specific degeneration in neurodegenerative pathology. In sum, the approach can reveal complex intravoxel tissue structure previously thought to be beyond the scope of diffusion imaging methodology.</Abstract>
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