Estimating Reference Bony Shape Models for Orthognathic Surgical Planning Using 3D Point-Cloud Deep Learning

Autor: Yankun Lang, Steve Guofang Shen, Tianshu Kuang, Daeseung Kim, Chunfeng Lian, Qin Liu, James J. Xia, Hannah Deng, Pew Thian Yap, Xu Chen, Deqiang Xiao, Lei Ma, Jaime Gateno

Publikováno v: IEEE J Biomed Health Inform

Orthognathic surgical outcomes rely heavily on the quality of surgical planning. Automatic estimation of a reference facial bone shape significantly reduces experience-dependent variability and improves planning accuracy and efficiency. We propose an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a63aa05097961e1cd98273041df0f304
https://doi.org/10.1109/jbhi.2021.3054494

Deep Simulation of Facial Appearance Changes Following Craniomaxillofacial Bony Movements in Orthognathic Surgical Planning

Autor: Deqiang Xiao, Hannah H. Deng, Pew Thian Yap, Chunfeng Lian, Qin Liu, Daeseung Kim, Tianshu Kuang, Lei Ma, Jaime Gateno, James J. Xia, Ye Wu, Michael A. K. Liebschner, Yankun Lang, Erkun Yang

Publikováno v: Med Image Comput Comput Assist Interv
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030872014
MICCAI (4)

Facial appearance changes with the movements of bony segments in orthognathic surgery of patients with craniomaxillofacial (CMF) deformities. Conventional bio-mechanical methods, such as finite element modeling (FEM), for simulating such changes, are

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2626f03274f6ee06ce6edc3c13805336
https://pubmed.ncbi.nlm.nih.gov/34966912

Unsupervised learning of reference bony shapes for orthognathic surgical planning with a surface deformation network

Autor: Tianshu Kuang, Lei Ma, Dinggang Shen, James J. Xia, Chunfeng Lian, Deqiang Xiao, Jaime Gateno, Hannah Deng, Steve Guo Fang Shen, Qin Liu, Pew Thian Yap, Daeseung Kim, Xu Chen, Yankun Lang

Publikováno v: Med Phys

PURPOSE: The purpose of this study was to reduce the experience dependence during the orthognathic surgical planning that involves virtually simulating the corrective procedure for jaw deformities. METHODS: We introduce a geometric deep learning fram

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2953abe6ef5f39bd6baf4ba55b99bfb
https://pubmed.ncbi.nlm.nih.gov/34309844

A Self-Supervised Deep Framework for Reference Bony Shape Estimation in Orthognathic Surgical Planning

Autor: Tianshu Kuang, Steve Guofang Shen, Daeseung Kim, Hannah Deng, Yankun Lang, Chunfeng Lian, Xu Chen, Lei Ma, James J. Xia, Deqiang Xiao, Pew Thian Yap, Jaime Gateno, Qin Liu, Dinggang Shen

Publikováno v: Med Image Comput Comput Assist Interv
Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030872014
MICCAI (4)

Virtual orthognathic surgical planning involves simulating surgical corrections of jaw deformities on 3D facial bony shape models. Due to the lack of necessary guidance, the planning procedure is highly experience-dependent and the planning results a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5cb369a75d35172823ed0279d26b3d27
https://europepmc.org/articles/PMC8674926/

A novel method for designing compressed sensing matrix

Autor: Shota Ishikawa, Waiyuan Wu, Yankun Lang

Publikováno v: 2018 International Workshop on Advanced Image Technology (IWAIT).

Compressed Sensing (CS) is a method to restore sparse signals from a small number of observed components using a CS-matrix, and is usually applied to data compression. In previous studies, Random-Matrix, whose elements are randomly generated variable

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8d91849b02ff3de99c7024493dbf1649
https://doi.org/10.1109/iwait.2018.8369747