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dc.contributor.authorMaximilian, Weiherer-
dc.contributor.authorAndreas, Eigenberger-
dc.contributor.authorBernhard, Egger-
dc.date.accessioned2023-03-31T04:35:27Z-
dc.date.available2023-03-31T04:35:27Z-
dc.date.issued2023-
dc.identifier.otherhttps://link.springer.com/article/10.1007/s00371-022-02431-3-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/7377-
dc.descriptionCC BYvi
dc.description.abstractWe 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.vi
dc.language.isoenvi
dc.publisherSpringervi
dc.subjectRBSMvi
dc.subject3D statistical shapevi
dc.titleLearning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scansvi
dc.typeBookvi
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