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A Prototype Representation to Approximate White Matter Bundles with Weighted Currents

  • Pietro Gori
  • Olivier Colliot
  • Linda Marrakchi-Kacem
  • Yulia Worbe
  • Fabrizio De Vico Fallani
  • Mario Chavez
  • Sophie Lecomte
  • Cyril Poupon
  • Andreas Hartmann
  • Nicholas Ayache
  • Stanley Durrleman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8675)

Abstract

Quantitative and qualitative analysis of white matter fibers resulting from tractography algorithms is made difficult by their huge number. To this end, we propose an approximation scheme which gives as result a more concise but at the same time exhaustive representation of a fiber bundle. It is based on a novel computational model for fibers, called weighted currents, characterised by a metric that considers both the pathway and the anatomical locations of the endpoints of the fibers. Similarity has therefore a twofold connotation: geometrical and related to the connectivity. The core idea is to use this metric for approximating a fiber bundle with a set of weighted prototypes, chosen among the fibers, which represent ensembles of similar fibers. The weights are related to the number of fibers represented by the prototypes. The algorithm is divided into two steps. First, the main modes of the fiber bundle are detected using a modularity based clustering algorithm. Second, a prototype fiber selection process is carried on in each cluster separately. This permits to explain the main patterns of the fiber bundle in a fast and accurate way.

Keywords

White Matter Approximation Scheme Fiber Bundle Gaussian Mixture Model White Matter Tract 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Pietro Gori
    • 1
  • Olivier Colliot
    • 1
  • Linda Marrakchi-Kacem
    • 1
    • 2
  • Yulia Worbe
    • 1
  • Fabrizio De Vico Fallani
    • 1
  • Mario Chavez
    • 1
  • Sophie Lecomte
    • 1
    • 2
  • Cyril Poupon
    • 2
  • Andreas Hartmann
    • 1
  • Nicholas Ayache
    • 3
  • Stanley Durrleman
    • 1
  1. 1.Inria Paris-Rocquencourt, Sorbonne Universités, UPMC Univ Paris 06 UMR S1127, Inserm U1127, CNRS UMR 7225, ICMParisFrance
  2. 2.Neurospin, CEAGif-Sur-YvetteFrance
  3. 3.Asclepios project-teamInria Sophia AntipolisSophia AntipolisFrance

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