Paper 13.098

D. Li et al., "Computation of Breast Ptosis from 3D Scans of Torso", in Proc. of 4th Int. Conf. on 3D Body Scanning Technologies, Long Beach CA, USA, 2013, pp. 98-106,


Computation of Breast Ptosis from 3D Scans of Torso


Danni LI 1, Lijuan ZHAO 2, Gregory P. REECE 3, Melissa A. CROSBY 3, Michelle C. FINGERET 3,4, Fatima A. MERCHANT 1,2,5

1 Dept. of Electrical and Computer Engineering, University of Houston, Houston, TX, USA;
2 Dept. of Computer Science, University of Houston, Houston, TX, USA;
3 Dept. of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA;
4 Dept. of Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA;
5 Dept. of Engineering Technology, University of Houston, Houston, TX, USA


Ptosis is an important morphological parameter for characterizing breast aesthetics and is frequently assessed before breast surgery. It refers to the extent to which the nipple is lower than the inframammary fold (the contour along which the inferior part of the breast attaches to the chest wall). Current clinical assessment of ptosis involves qualitative visualization by observers, which is subject to inter- and intra-observer variability. Alternatively, ptosis can be measured anthropometrically directly by manual measurements from the patient or indirectly from manual or computerized measurements on clinical photographs. Although functional, these methods are subject to operator bias and can be practically limiting. As stereophotography is now finding its niche in clinical breast surgery, in this study we investigated and evaluated the utility of three-dimensional (3D) features such as surface curvature, coronal projection and surface normal for the assessment of breast ptosis using 3D scans of the torso. Experimental results suggest that 3D features are successful for objectively categorizing breast ptosis with high accuracy and precision.


3D image, Breast surgery, Ptosis, Gaussian curvature, Coronal projection, Classification


Full paper: 13.098.pdf
Proceedings: 3DBST 2013, 19-20 Nov. 2013, Long Beach California, USA
Pages: 98-106

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