Reference : A rigged model of the breast for preoperative surgical planning
E-prints/Working papers : Already available on another site
Engineering, computing & technology : Materials science & engineering
Engineering, computing & technology : Mechanical engineering
Engineering, computing & technology : Multidisciplinary, general & others
Computational Sciences
http://hdl.handle.net/10993/47407
A rigged model of the breast for preoperative surgical planning
English
Mazier, Arnaud mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
Ribes, Sophie mailto []
Testylier, Romain mailto []
Van Meer, Frédérick mailto []
Gilles, Benjamin mailto []
Faure, François mailto []
Bordas, Stéphane mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
2021
Submitted preprint
22
No
[en] Surgical planning ; model-based registration ; animation ; anatomical variability ; breast
[en] In breast surgical practice, various scans and medical examinations are performed before surgery. This includes identifying landmarks defining the operating procedure. In most cases, the position of the patient during the scan is vastly different from the one encountered during the operation. We address the challenge of mapping preoperative information to the operating field, with the following constraints: registration has to be done in less than 10 seconds to be compatible with a clinical workflow; the cost of the device must be small and we assume data scarcity, i.e. that our database has twenty scans of patients at most. We build anatomical complexity through a skinning model comprised of scalable bones (to account for pose and morphological variations) and deformable organs (blendshapes, to account for anatomical variations). Similar to animation rigs used in computer graphics, and in contrast to statistical approaches, we manually design a model with some desirable properties, using a reduced number of well-chosen degrees of freedom. Meaningful constraints can be applied to the registration depending on the context, and the trade-off between precision and complexity can be optimized. The result is a surface mesh of the patient obtained in less than 1 minute (scan and reconstruction included) and a registration method that converges within a few seconds (3 maximum), reaching a mean absolute squared error of 2.3 mm for mesh registration and 8.0 mm for anatomical landmarks. The registered model is used to transfer surgical reference patterns on any patient in any position.
Researchers
http://hdl.handle.net/10993/47407
This study was supported by European Union’s Horizon 2020 research and innovation program under grant agreement No 811099 and the Marie Sklodowska-Curie grant agreement No. 764644. The medical images used in the present study were obtained in Hopital Arnaud de Villeneuve, Département de Gynécologie Obstétrique in collaboration with Dr Gauthier Rathat.
https://arxiv.org/abs/2105.00763
H2020 ; 764644 - RAINBOW - Rapid Biomechanics Simulation for Personalized Clinical Design

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