Segmentation of nerve bundles and ganglia in spine MRI using particle filters
Name
818357131-MIT.pdf
Description
Full printable version
Size
4.08 MB
Format
Adobe PDF
Checksum (MD5)
5d42bcad3f3967c04ae0d35e4c14fff3
Author(s)
Dalca, Adrian Vasile
Advisor(s)
Polina Golland.
Date Issued
2012
Publisher
Massachusetts Institute of Technology
Abstract
Automatic segmentation of spinal nerve bundles originating within the dural sac and exiting the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this thesis, we present an automatic tracking method for segmentation of nerve bundles based on particle filters. We develop a novel approach to flexible particle representation of tubular structures based on Bezier splines. We construct an appropriate dynamics to reflect the continuity and smoothness properties of real nerve bundles. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We evaluate the results by comparing them to expert manual segmentation, and we demonstrate accurate and fast nerve tracking.
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. 41-44).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
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