Importance sampling spherical harmonics to improve probabilistic tractography

H. Ertan Cetingul, Laura Dumont, Mariappan S. Nadar, Paul M. Thompson, Guillermo Sapiro, Christophe Lenglet

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We consider the problem of improving the accuracy and reliability of probabilistic white matter tractography methods by improving the built-in sampling scheme, which randomly draws, from a diffusion model such as the orientation distribution function (ODF), a direction of propagation. Existing methods employing inverse transform sampling require an ad hoc thresholding step to prevent the less likely directions from being sampled. We herein propose to perform importance sampling of spherical harmonics, which redistributes an input point set on the sphere to match the ODF using hierarchical sample warping. This produces a point set that is more concentrated around the modes, allowing the subsequent inverse transform sampling to generate orientations that are in better accordance with the local fiber configuration. Integrated into a Kalman filter-based framework, our approach is evaluated through experiments on synthetic, phantom, and real datasets.

Original languageEnglish
Title of host publicationProceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013
Pages46-49
Number of pages4
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013 - Philadelphia, PA, United States
Duration: 22 Jun 201324 Jun 2013

Publication series

NameProceedings - 2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013

Conference

Conference2013 3rd International Workshop on Pattern Recognition in Neuroimaging, PRNI 2013
Country/TerritoryUnited States
CityPhiladelphia, PA
Period22/06/1324/06/13

Keywords

  • Kalman filter
  • diffusion MRI
  • harmonic analysis
  • sampling theory
  • white matter

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