Deep Learning-Based CT Radiomics for Feature Representation and Analysis of Aging Characteristics of Asian Bony Orbit.

Journal: The Journal of craniofacial surgery
PMID: 34560737

Abstract

OBJECTIVE: This paper puts forward a new method for automatic segmentation of bony orbit as well as automatic extraction and classification of aging features of segmented orbit contour based on depth learning, with which the aging mode of bony orbit contour is preliminarily validated.

Authors

  • Zhu Li
    School of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310018, China. Electronic address: lz1126@hdu.edu.cn.
  • Kunjian Chen
    School of Electronics and Information, Hangzhou Dianzi University.
  • Jiayu Yang
    School of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Lei Pan
    Department of Chemical Engineering, Michigan Technological University, Houghton, MI 49931, USA.
  • Zhen Wang
    Department of Otolaryngology, Longgang Otolaryngology hospital & Shenzhen Key Laboratory of Otolaryngology, Shenzhen Institute of Otolaryngology, Shenzhen, Guangdong, China.
  • Panfeng Yang
    Department of Radiology, People's Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, Hangzhou, China.
  • Sufan Wu
    Department of Plastic and Reconstructive Surgery.
  • Jingyu Li
    Medical Technology Department, Qiqihar Medical University, Qiqihar 161006, Heilongjiang, China.

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