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Proceedings Paper

Automatic surface correspondence methods for a deformed breast
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Paper Abstract

A significant amount of breast cancer research in recent years has been devoted to novel means of tumor detection such as MR contrast enhancement, electrical impedance tomography, microwave imaging, and elastography. Many of these detection methods involve deforming the breast. Often, these deformed images need to be correlated to anatomical images of the breast in a different configuration. In the case of our elastography framework, a series of comparisons between the pre- and post-deformed images needs to be performed. This paper presents an automatic method for determining correspondence between images of a pendant breast and a partially-constrained, compressed breast. The algorithm is an extension to the symmetric closest point approach of Papademetris et al. However, because of the unique deformation and shape change of a partially-constrained, compressed breast, the algorithm was modified through the use of iterative closest point (ICP) registration on easily identifiable sections of the breast images and through weighting the symmetric nearest neighbor correspondence. The algorithm presented in this paper significantly improves correspondence determination between the pre- and post-deformed images for a simulation when compared to the original Papademetris et al.'s symmetric closest point criteria.

Paper Details

Date Published: 10 March 2006
PDF: 8 pages
Proc. SPIE 6141, Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display, 614125 (10 March 2006); doi: 10.1117/12.651720
Show Author Affiliations
Daniel R. Schuler, Vanderbilt Univ. (United States)
Jao J. Ou, Vanderbilt Univ. (United States)
Stephanie L. Barnes, Vanderbilt Univ. (United States)
Michael I. Miga, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 6141:
Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display
Kevin R. Cleary; Robert L. Galloway, Jr., Editor(s)

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