Locally-Constrained Region-Based Methods for DW-MRI Segmentation

Abstract

In this paper, we describe a method for segmenting fiber bundles from diffusion-weighted magnetic resonance images using a locally-constrained region based approach. From a pre-computed optimal path, the algorithm propagates outward capturing only those voxels which are locally connected to the fiber bundle. Rather than attempting to find large numbers of open curves or single fibers, which individually have questionable meaning, this method segments the full fiber bundle region. The strengths of this approach include its ease-of-use, computational speed, and applicability to a wide range of fiber bundles. In this work, we show results for segmenting the cingulum bundle. Finally, we explain how this approach and extensions thereto overcome a major problem that typical region-based flows experience when attempting to segment neural fiber bundles.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2007
Accession Number
ADA481866

Entities

People

  • Allen Tannenbaum
  • James V. Miller
  • John Melonakos
  • Marc Niethammer
  • Marek Kubicki
  • Vandana Mohan

Organizations

  • Georgia Tech

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Anisotropy
  • Bayesian Networks
  • Boundaries
  • Brain
  • Computational Science
  • Computer Vision
  • Diffusion
  • Eigenvectors
  • Equations
  • Geodesics
  • Graphics Processing Unit
  • Health Services
  • Image Segmentation
  • Orientation (Direction)
  • Probability
  • Three Dimensional

Readers

  • Computer Vision.
  • Medical Imaging.
  • Reinforced Composite Materials