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Proceedings Paper

Improvements in level set segmentation of 3D small animal imagery
Author(s): Jeffery R Price; Deniz Aykac; Jonathan Wall
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Paper Abstract

In this paper, we investigate several improvements to region-based level set algorithms in the context of segmenting x-ray CT data from pre-clinical imaging of small animal models. We incorporate a recently introduced signed distance preserving term into a region-based level set model and provide formulas for a semi-implicit finite difference implementation. We illustrate some pitfalls of topology preserving level sets and introduce the concept of connectivity preservation as a potential alternative. We illustrate the benefits of these improvements on phantom and real data.

Paper Details

Date Published: 5 March 2007
PDF: 10 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651233 (5 March 2007); doi: 10.1117/12.709662
Show Author Affiliations
Jeffery R Price, Oak Ridge National Lab. (United States)
Deniz Aykac, Oak Ridge National Lab. (United States)
Jonathan Wall, Univ. of Tennessee (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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