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

Weiherer, Maximilian and Eigenberger, Andreas and Egger, Bernhard and Brebant, Vanessa and Prantl, Lukas and Palm, Christoph (2023) Learning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scans. VISUAL COMPUTER, 39 (4). pp. 1597-1616. ISSN 0178-2789, 1432-2315

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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 0.17mm and a specificity of 2.8mm. 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/.

Item Type: Article
Uncontrolled Keywords: SIMULATION; RECONSTRUCTION; DEFORMATIONS; SPACE; Statistical shape model; Non-rigid surface registration; Breast imaging; Surgical outcome simulation; Breast reconstruction surgery
Subjects: 000 Computer science, information & general works > 004 Computer science
600 Technology > 610 Medical sciences Medicine
Divisions: Medicine > Zentren des Universitätsklinikums Regensburg > Zentrum für Plastische-, Hand- und Wiederherstellungschirurgie
Depositing User: Dr. Gernot Deinzer
Date Deposited: 20 Feb 2024 09:40
Last Modified: 20 Feb 2024 09:40
URI: https://pred.uni-regensburg.de/id/eprint/56445

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