
Proceedings Paper
Objective assessment of the aesthetic outcomes of breast cancer treatment: toward automatic localization of fiducial points on digital photographsFormat | Member Price | Non-Member Price |
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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
Published in SPIE Proceedings Vol. 6514:
Medical Imaging 2007: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)
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)
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)
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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