Learning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scans

Abstract

We present the Regensburg Breast Shape Model (RBSM)—a 3D statistical shape model of the female breast built from 110 breast scans acquired in a standing position, and the first publicly available. Together with the model, a fully automated, pairwise surface registration pipeline used to establish dense correspondence among 3D breast scans is introduced. Our method is computationally efficient and requires only four landmarks to guide the registration process. A major challenge when modeling female breasts from surface-only 3D breast scans is the non-separability of breast and thorax. In order to weaken the strong coupling between breast and surrounding areas, we propose to minimize the variance outside the breast region as much as possible. To achieve this goal, a novel concept called breast probability masks (BPMs) is introduced. A BPM assigns probabilities to each point of a 3D breast scan, telling how likely it is that a particular point belongs to the breast area. During registration, we use BPMs to align the template to the target as accurately as possible inside the breast region and only roughly outside. This simple yet effective strategy significantly reduces the unwanted variance outside the breast region, leading to better statistical shape models in which breast shapes are quite well decoupled from the thorax. The RBSM is thus able to produce a variety of different breast shapes as independently as possible from the shape of the thorax. Our systematic experimental evaluation reveals a generalization ability of 0.17 mm and a specificity of 2.8 mm. To underline the expressiveness of the proposed model, we finally demonstrate in two showcase applications how the RBSM can be used for surgical outcome simulation and the prediction of a missing breast from the remaining one. Our model is available at https://www.rbsm.re-mic.de/.

Fast and Simple Statistical Shape Analysis of Pregnant Women Using Radial Deformation of a Cylindrical Template

“…3) from affecting the model. The segmented torso region might still be affected by pose-related variations arising from presence of quasisimilar postures [30]. The choice of cylindrical template was inspired by previous studies [31], [32], which used either cylinders or truncated cones as part of the template to model the human shape.…”

“…The compactness of the model, which was developed using all the 225 scans, was defined as the ratio of the total variance explained by the principal vectors. The generalization error was calculated using leaveone-out cross-validation for all the 225 scans [30] and the specificity was calculated as the average minimum distance of uniformly distributed, randomly generated scans (n=100) from the training set (n=225) [29].…”

Precise Monitoring of Returning Sensation in Digital Nerve Lesions by 3-D Imaging: A Proof-of-Concept Study

“…[8][9][10][11][12][13] Three-dimensional imaging devices recently emerged to allow objective quantification of disparity in projection, volume, and surface symmetry in various medical conditions. [14][15][16][17] Despite its tremendous potential, 3D surface imaging has not been applied in hand surgery to this point. Nevertheless, previous studies demonstrated the capability of patients to precisely outline the border of the AA precisely after digital-nerve repair.…”