Computation of breast ptosis from 3D surface scans of the female torso.

Autor: Li D; Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204, USA., Cheong A; Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204, USA., Reece GP; Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Crosby MA; Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Fingeret MC; Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA., Merchant FA; Department of Electrical and Computer Engineering, University of Houston, Houston, TX 77204, USA; Department of Engineering Technology, University of Houston, Houston, TX 77204, USA. Electronic address: fmerchant@uh.edu.
Jazyk: angličtina
Zdroj: Computers in biology and medicine [Comput Biol Med] 2016 Nov 01; Vol. 78, pp. 18-28. Date of Electronic Publication: 2016 Sep 09.
DOI: 10.1016/j.compbiomed.2016.09.002
Abstrakt: Stereophotography is now finding a niche in clinical breast surgery, and several methods for quantitatively measuring breast morphology from 3D surface images have been developed. Breast ptosis (sagging of the breast), which refers to the extent by which the nipple is lower than the inframammary fold (the contour along which the inferior part of the breast attaches to the chest wall), is an important morphological parameter that is frequently used for assessing the outcome of breast surgery. This study presents a novel algorithm that utilizes three-dimensional (3D) features such as surface curvature and orientation for the assessment of breast ptosis from 3D scans of the female torso. The performance of the computational approach proposed was compared against the consensus of manual ptosis ratings by nine plastic surgeons, and that of current 2D photogrammetric methods. Compared to the 2D methods, the average accuracy for 3D features was ~13% higher, with an increase in precision, recall, and F-score of 37%, 29%, and 33%, respectively. The computational approach proposed provides an improved and unbiased objective method for rating ptosis when compared to qualitative visualization by observers, and distance based 2D photogrammetry approaches.
Competing Interests: Conflicts of Interest: None declared.
(Copyright © 2016 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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