Estimating Reference Shape Model for Personalized Surgical Reconstruction of Craniomaxillofacial Defects

Deqiang Xiao, Chunfeng Lian, Li Wang, Hannah Deng, Hung Ying Lin, Kim Han Thung, Jihua Zhu, Peng Yuan, Leonel Perez, Jaime Gateno, Steve Guofang Shen, Pew Thian Yap, James J. Xia, DInggang Shen

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Objective: To estimate a patient-specific reference bone shape model for a patient with craniomaxillofacial (CMF) defects due to facial trauma. Methods: We proposed an automatic facial bone shape estimation framework using pre-traumatic conventional portrait photos and post-traumatic head computed tomography (CT) scans via a 3D face reconstruction and a deformable shape model. Specifically, a three-dimensional (3D) face was first reconstructed from the patient's pre-traumatic portrait photos. Second, a correlation model between the skin and bone surfaces was constructed using a sparse representation based on the CT images of training normal subjects. Third, by feeding the reconstructed 3D face into the correlation model, an initial reference shape model was generated. In addition, we refined the initial estimation by applying non-rigid surface matching between the initially estimated shape and the patient's post-traumatic bone based on the adaptive-focus deformable shape model (AFDSM). Furthermore, a statistical shape model, built from the training normal subjects, was utilized to constrain the deformation process to avoid overfitting. Results and Conclusion: The proposed method was evaluated using both synthetic and real patient data. Experimental results show that the patient's abnormal facial bony structure can be recovered using our method, and the estimated reference shape model is considered clinically acceptable by an experienced CMF surgeon. Significance: The proposed method is more suitable to the complex CMF defects for CMF reconstructive surgical planning.

Original languageEnglish (US)
Article number9079472
Pages (from-to)362-373
Number of pages12
JournalIEEE Transactions on Biomedical Engineering
Volume68
Issue number2
DOIs
StatePublished - Feb 2021

Keywords

  • Adaptive-focus deformable shape model (AFDSM)
  • craniomaxillofacial (CMF) surgical planning
  • sparse representation
  • statistical shape model (SSM)
  • three-dimensional (3D) face reconstruction

ASJC Scopus subject areas

  • Biomedical Engineering

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