iRBSM: A Deep Implicit 3D Breast Shape Model

  • We present the first deep implicit 3D shape model of the female breast, building upon and improving the recently proposed Regensburg Breast Shape Model (RBSM). Compared to its PCA-based predecessor, our model employs implicit neural representations; hence, it can be trained on raw 3D breast scans and eliminates the need for computationally demanding non-rigid registration, a task that isWe present the first deep implicit 3D shape model of the female breast, building upon and improving the recently proposed Regensburg Breast Shape Model (RBSM). Compared to its PCA-based predecessor, our model employs implicit neural representations; hence, it can be trained on raw 3D breast scans and eliminates the need for computationally demanding non-rigid registration, a task that is particularly difficult for feature-less breast shapes. The resulting model, dubbed iRBSM, captures detailed surface geometry including fine structures such as nipples and belly buttons, is highly expressive, and outperforms the RBSM on different surface reconstruction tasks. Finally, leveraging the iRBSM, we present a prototype application to 3D reconstruct breast shapes from just a single image. Model and code publicly available at https://rbsm.re-mic.de/implicit.show moreshow less

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics
Metadaten
Author:Maximilian Weiherer, Antonia von Riedheim, Vanessa BrébantORCiD, Bernhard EggerORCiD, Christoph PalmORCiDGND
DOI:https://doi.org/10.1007/978-3-658-47422-5_11
Parent Title (German):Bildverarbeitung für die Medizin 2025: Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025
Publisher:Springer Vieweg
Place of publication:Wiesbaden
Editor:Christoph PalmORCiDGND, Katharina Breininger, Thomas M. DesernoORCiD, Heinz HandelsORCiD, Andreas MaierORCiD, Klaus H. Maier-HeinORCiD, Thomas Tolxdorff
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2025
Release Date:2025/04/28
First Page:38
Last Page:43
Andere Schriftenreihe:Informatik aktuell
Institutes:Fakultät Informatik und Mathematik
Regensburg Center of Health Sciences and Technology - RCHST
Fakultät Informatik und Mathematik / Labor Regensburg Medical Image Computing (ReMIC)
Begutachtungsstatus:peer-reviewed
research focus:Lebenswissenschaften und Ethik
Licence (German):Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG
Einverstanden ✔
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.