Mr. Daniel R. Schuler Profile

Daniel R. Schuler

at Vanderbilt Univ

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Proceedings Article | 10 March 2006 Paper

Automatic surface correspondence methods for a deformed breast

Daniel Schuler, Jao Ou, Stephanie Barnes, Michael Miga

Proceedings Volume 6141, 614125 (2006) https://doi.org/10.1117/12.651720

KEYWORDS: Breast, Clouds, Nipple, Computer simulations, Elastography, Detection and tracking algorithms, Breast cancer, Image compression, Image registration, Matrices

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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.

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