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Proceedings Paper

Parsimonious model selection for tissue classification: a DTI study of zebrafish
Author(s): Raisa Z. Freidlin; Michal E. Komlosh; Murray H. Loew; Peter J. Basser
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Paper Abstract

One aim of this work is to investigate the feasibility of using a hierarchy of models to describe diffusion tensor MRI data. Parsimonious model selection criteria are used to choose among different models of diffusion within tissue. Second, based on this information, we assess whether we can perform simultaneous tissue segmentation and classification. The proposed hierarchical framework used for parsimonious model selection is based on the F-test, adapted from Snedecor. Diffusion Magnetic Resonance Microscopy (MRM) provides near-microscopic resolution without relying on a sample's optical transparency for image formation. Diffusion MRM is a noninvasive imaging technique for quantitative analysis of intrinsic features of tissues. Thus, we propose using Diffusion MRM to characterize normal tissue structure in adult zebrafish, and possibly subtle anatomical or structural differences between normals and knockouts. Both numerical phantoms and diffusion weighted image (DWI) data obtained from adult zebrafish are used to test this model selection framework.

Paper Details

Date Published: 8 March 2007
PDF: 11 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65122T (8 March 2007); doi: 10.1117/12.708312
Show Author Affiliations
Raisa Z. Freidlin, National Institutes of Health (United States)
George Washington Univ. (United States)
Michal E. Komlosh, National Institutes of Health (United States)
Murray H. Loew, George Washington Univ. (United States)
Peter J. Basser, National Institutes of Health (United States)

Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)

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