A Point Cloud Generation Network for Automatic Prediction of Postoperative Maxillofacial Soft Tissue.

Journal: Annals of biomedical engineering
Published Date: May 16, 2025

Abstract

PURPOSE: In the planning of maxillofacial surgery, accurately evaluating the postoperative soft tissue area is crucial. This allows doctors to provide patients with better morphological recovery while ensuring the restoration of normal functional areas. This study aims to develop an advanced automatic algorithm for the completion of soft tissue defects, enhancing the accuracy and effectiveness of surgical planning.

Authors

  • Ruiyang Li
    2State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong China.
  • Bimeng Jie
  • Boxuan Han
    School of Biomedical Engineering, Tsinghua University, Beijing, 100084, China.
  • Yuchao Zheng
    School of Biomedical Engineering, Tsinghua University, Beijing, 100084, China.
  • Chengyi Wang
    School of Life Sciences, Tiangong University, 399 Binshui West Road, Tianjin 300387, China.
  • Xuan Yang
    Dongfang College, Zhejiang University of Finance & Economics, Haining 314408, Zhejiang, China. yx_321@zufe.edu.cn.
  • Yi Zhang
    Department of Thyroid Surgery, China-Japan Union Hospital of Jilin University, Jilin University, Changchun, China.
  • Hongen Liao
  • Yang He
    Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhenjiang Province, China.
  • Longfei Ma
    Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.

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