Automatic CT image segmentation of maxillary sinus based on VGG network and improved V-Net.

Journal: International journal of computer assisted radiology and surgery
Published Date: Jul 16, 2020

Abstract

PURPOSE: The analysis of the maxillary sinus (MS) can provide an assessment for many clinical diagnoses, so accurate CT image segmentation of the MS is essential. However, common segmentation methods are mainly done by experienced doctors manually, and there are some challenges such as low efficiency and precision. As for automatic methods, the initial seed points and adjustment of various parameters are required, which will affect the segmentation efficiency. Thus, accurate, efficient, and automatic segmentation method of MS is critical to promote the clinical application.

Authors

  • Jiangchang Xu
    Institute of Biomedical Manufacturing and Life Quality Engineering, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University , Shanghai , China.
  • Shiming Wang
    Institute of Biomedical Manufacturing and Life Quality Engineering, State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University , Shanghai , China.
  • Zijie Zhou
    Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Jiannan Liu
    Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Xiaoyi Jiang
    Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany.
  • Xiaojun Chen
    Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.

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