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Deep learning for biomechanical modeling of facial tissue deformation in orthognathic surgical planning.

, , , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 17 (5): 945-952 (2022)

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Estimating Reference Shape Model for Personalized Surgical Reconstruction of Craniomaxillofacial Defects., , , , , , , , , and 4 other author(s). IEEE Trans. Biomed. Eng., 68 (2): 362-373 (2021)Three-dimensional virtual-reality surgical planning and soft-tissue prediction for orthognathic surgery., , , , , , , , and . IEEE Trans. Inf. Technol. Biomed., 5 (2): 97-107 (2001)DLLNet: An Attention-Based Deep Learning Method for Dental Landmark Localization on High-Resolution 3D Digital Dental Models., , , , , , , and . MICCAI (4), volume 12904 of Lecture Notes in Computer Science, page 478-487. Springer, (2021)A Novel Computer-Aided Surgical Simulation (CASS) System to Streamline Orthognathic Surgical Planning., , , , , , , , , and 2 other author(s). MIAR, volume 9805 of Lecture Notes in Computer Science, page 3-14. Springer, (2016)Incremental Kernel Ridge Regression for the Prediction of Soft Tissue Deformations., , , , , , , , and . MICCAI (1), volume 7510 of Lecture Notes in Computer Science, page 99-106. Springer, (2012)Simulation of Postoperative Facial Appearances via Geometric Deep Learning for Efficient Orthognathic Surgical Planning., , , , , , , , , and 2 other author(s). IEEE Trans. Medical Imaging, 42 (2): 336-345 (February 2023)A novel incremental simulation of facial changes following orthognathic surgery using FEM with realistic lip sliding effect., , , , , , , , , and . Medical Image Anal., (2021)Deep learning for biomechanical modeling of facial tissue deformation in orthognathic surgical planning., , , , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 17 (5): 945-952 (2022)A Self-supervised Deep Framework for Reference Bony Shape Estimation in Orthognathic Surgical Planning., , , , , , , , , and 4 other author(s). MICCAI (4), volume 12904 of Lecture Notes in Computer Science, page 469-477. Springer, (2021)SkullEngine: A Multi-stage CNN Framework for Collaborative CBCT Image Segmentation and Landmark Detection., , , , , , , , , and 1 other author(s). MLMI@MICCAI, volume 12966 of Lecture Notes in Computer Science, page 606-614. Springer, (2021)