Sheet-Like White Matter Fiber Tracts: Representation, Clustering, and Quantitative Analysis

  • Mahnaz Maddah
  • James V. Miller
  • Edith V. Sullivan
  • Adolf Pfefferbaum
  • Torsten Rohlfing
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6892)

Abstract

We introduce an automated and probabilistic method for subject-specific segmentation of sheet-like fiber tracts. In addition to clustering of trajectories into anatomically meaningful bundles, the method provides statistics of diffusion measures by establishing point correspondences on the estimated medial representation of each bundle. We also introduce a new approach for medial surface generation of sheet-like fiber bundles in order too initialize the proposed clustering algorithm. Applying the new method to a population study of brain aging on 24 subjects demonstrates the capabilities and strengths of the algorithm in identifying and visualizing spatial patterns of group differences.

Keywords

Corpus Callosum Medial Surface Orientation Information Medial Representation Diffusion Measure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mahnaz Maddah
    • 1
  • James V. Miller
    • 2
  • Edith V. Sullivan
    • 1
    • 3
  • Adolf Pfefferbaum
    • 1
    • 3
  • Torsten Rohlfing
    • 1
  1. 1.Neuroscience ProgramSRI InternationalMenlo ParkUSA
  2. 2.Interventional and TherapyGE Global ResearchNiskayunaUSA
  3. 3.Dept. of Psychiatry and Behavioral SciencesStanford UniversityStanfordUSA

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