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Proceedings Paper

Measures for validation of DTI tractography
Author(s): Sylvain Gouttard; Casey B. Goodlett; Marek Kubicki; Guido Gerig
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Paper Abstract

The evaluation of analysis methods for diffusion tensor imaging (DTI) remains challenging due to the lack of gold standards and validation frameworks. Significant work remains in developing metrics for comparing fiber bundles generated from streamline tractography. We propose a set of volumetric and tract oriented measures for evaluating tract differences. The different methodsdeveloped for this assessment work are: an overlap measurement, a point cloud distance and a quantification of the diffusion properties at similar locations between fiber bundles. The application of the measures in this paper is a comparison of atlas generated tractography to tractography generated in individual images. For the validation we used a database of 37 subject DTIs, and applied the measurements on five specific fiber bundles: uncinate, cingulum (left and right for both bundles) and genu. Each measurments is interesting for specific use: the overlap measure presents a simple and comprehensive metric but is sensitive to partial voluming and does not give consistent values depending on the bundle geometry. The point cloud distance associated with a quantile interpretation of the distribution gives a good intuition of how close and similar the bundles are. Finally, the functional difference is useful for a comparison of the diffusion properties since it is the focus of many DTI analysis to compare scalar invariants. The comparison demonstrated reasonable similarity of results. The tract difference measures are also applicable to comparison of tractography algorithms, quality control, reproducibility studies, and other validation problems.

Paper Details

Date Published: 14 February 2012
PDF: 6 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83140J (14 February 2012); doi: 10.1117/12.911546
Show Author Affiliations
Sylvain Gouttard, The Univ. of Utah (United States)
Casey B. Goodlett, Kitware, Inc. (United States)
Marek Kubicki, Harvard Medical School (United States)
Guido Gerig, The Univ. of Utah (United States)


Published in SPIE Proceedings Vol. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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