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Proceedings Paper

Objective assessment of the aesthetic outcomes of breast cancer treatment: toward automatic localization of fiducial points on digital photographs
Author(s): Nitin Udpa; Mehul P. Sampat; Min Soon Kim; Gregory P. Reece; Mia K. Markey
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Paper Abstract

The contemporary goals of breast cancer treatment are not limited to cure but include maximizing quality of life. All breast cancer treatment can adversely affect breast appearance. Developing objective, quantifiable methods to assess breast appearance is important to understand the impact of deformity on patient quality of life, guide selection of current treatments, and make rational treatment advances. A few measures of aesthetic properties such as symmetry have been developed. They are computed from the distances between manually identified fiducial points on digital photographs. However, this is time-consuming and subject to intra- and inter-observer variability. The purpose of this study is to investigate methods for automatic localization of fiducial points on anterior-posterior digital photographs taken to document the outcomes of breast reconstruction. Particular emphasis is placed on automatic localization of the nipple complex since the most widely used aesthetic measure, the Breast Retraction Assessment, quantifies the symmetry of nipple locations. The nipple complexes are automatically localized using normalized cross-correlation with a template bank of variants of Gaussian and Laplacian of Gaussian filters. A probability map of likely nipple locations determined from the image database is used to reduce the number of false positive detections from the matched filter operation. The accuracy of the nipple detection was evaluated relative to markings made by three human observers. The impact of using the fiducial point locations as identified by the automatic method, as opposed to the manual method, on the calculation of the Breast Retraction Assessment was also evaluated.

Paper Details

Date Published: 30 March 2007
PDF: 9 pages
Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 651420 (30 March 2007); doi: 10.1117/12.712236
Show Author Affiliations
Nitin Udpa, Univ. of Texas at Austin (United States)
Mehul P. Sampat, Univ. of Texas at Austin (United States)
Min Soon Kim, Univ. of Texas at Austin (United States)
Gregory P. Reece, The Univ. of Texas M. D. Anderson Cancer Ctr. (United States)
Mia K. Markey, Univ. of Texas at Austin (United States)

Published in SPIE Proceedings Vol. 6514:
Medical Imaging 2007: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

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