Abstract
In this paper, we propose a novel statistical deformable model for bone-related soft-tissue prediction, which we called Br-SDM. In Br-SDM, we have integrated Finite Element Model(FEM) and Statistical Deformable Model(SDM) to achieve both accurate and efficient prediction for orthognathic surgery planning. By combining FEM-based surgery simulation for sample generation and SDM for soft tissue prediction, we are able to capture the prior knowledge of bone-related soft-tissue deformation for different surgical plans. Then the post-operative appearance can be predicted in a more efficient way from a Br-SDM based optimization. Our experiments have shown that Br-SDM is able to give comparable soft-tissue prediction accuracy with respect to conventional FEM-based prediction while only requires 10% of its computational cost.
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Zhu, M.: Simulation and Prediction of Orthognathic Surgery on Skeletal Class III Deformation. In: 3rd Chinese International Congress on Oral and Maxillofacial Surgery, in conjunction with 6th National Congress on Oral and Maxillofacial Surgery, Kunming, Yunan, PRC, p. 338 (2002)
Keeve, E., Girod, S., et al.: Deformable Modeling of Facial Tissue for Craniofacial Surgery Simulation. Computer Aided Surgery 3, 228–238 (1998)
Bro-Nielsen, M., HTM Inc., Rockville, M.D.: Finite Element Modeling in Surgery Simulation. Proceedings of the IEEE 86(33), 490–503 (1998)
Mollemans, W., Schutyser, F., et al.: Predicting soft-tissue deformations for a maxillofacial surgery planning system: From computational strategies to a complete clinical validation. Medical Image Analysis 11(3), 282–301 (2007)
Roose, L., De Maerteleire, W., Mollemans, W., Suetens, P.: Validation of different soft tissue simulation methods for breast augmentation. In: Proceedings of CARS, pp. 485–490 (2005)
Cotin, S., et al.: A hybrid elastic model allowing real-time cutting, deformations and force feedback for surgery training and simulation. The Visual Computer 16(88), 437–452 (2000)
Meller, S., Nkenke, E., Kalender, W.: Statistical Face Models for the Prediction of Soft-tissue Deformations after Orthognathic Osteotomies. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 443–450. Springer, Heidelberg (2005)
Fung, Y.C.: Biomechanics: Mechanical Properties of Living Tissues, pp. 242–320. Springer, Heidelberg (1993)
Keeve, E., Girod, S., Pfeifle, P., Girod, B.: Anatomy-Based Facial Tissue Modeling Using the Finite Element Method. In: Proceedings of IEEE visualization 1996, p. 21 (1996)
Besl, P.J., Mckay, N.D.: A Method for Registration of 3D Shapes. IEEE Trans. on Pattern Anal. & Mach. Intell. 14(2), 239–256 (1992)
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© 2008 Springer-Verlag Berlin Heidelberg
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He, Q., Feng, J., Ip, H.H.S., Xia, J., Cao, X. (2008). An Integration of Statistical Deformable Model and Finite Element Method for Bone-Related Soft Tissue Prediction in Orthognathic Surgery Planning. In: Dohi, T., Sakuma, I., Liao, H. (eds) Medical Imaging and Augmented Reality. MIAR 2008. Lecture Notes in Computer Science, vol 5128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79982-5_4
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DOI: https://doi.org/10.1007/978-3-540-79982-5_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79981-8
Online ISBN: 978-3-540-79982-5
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