Scale- and Slice-aware Net (S aNet) for 3D segmentation of organs and musculoskeletal structures in pelvic MRI.

Journal: Magnetic resonance in medicine
Published Date: Aug 2, 2021

Abstract

PURPOSE: MRI of organs and musculoskeletal structures in the female pelvis presents a unique display of pelvic anatomy. Automated segmentation of pelvic structures plays an important role in personalized diagnosis and treatment on pelvic structures disease. Pelvic organ systems are very complicated, and it is a challenging task for 3D segmentation of massive pelvic structures on MRI.

Authors

  • Chaoyang Yan
    Institute for AI in Medicine, School of Automation, Nanjing University of Information Science and Technology, Nanjing, China.
  • Jing-Jing Lu
    Department of Radiology, Beijing United Family Hospital, Beijing, China.
  • Kang Chen
    Institute of Intelligent Control and Robotics, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
  • Haoda Lu
    School of Automation, Nanjing University of Information Science and Technology, Nanjing 210044, P.R.China;Jiangsu Key Laboratory of Large Data Analysis Technology, Nanjing 210044, P.R.China.
  • Li Yu
    Key Laboratory of Colloid and Interface Chemistry, Shandong University, Ministry of Education, Jinan 250100, P. R. China. ylmlt@sdu.edu.cn.
  • Mengyan Sun
    Department of Radiology, Beijing Chest Hospital, Capital Medical University, Beijing, China.
  • Jun Xu
    Department of Nephrology, The Affiliated Baiyun Hospital of Guizhou Medical University, Guizhou, China.

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