Automatic detection, segmentation, and classification of primary bone tumors and bone infections using an ensemble multi-task deep learning framework on multi-parametric MRIs: a multi-center study.

Journal: European radiology
Published Date: Dec 21, 2023

Abstract

OBJECTIVES: To develop an ensemble multi-task deep learning (DL) framework for automatic and simultaneous detection, segmentation, and classification of primary bone tumors (PBTs) and bone infections based on multi-parametric MRI from multi-center.

Authors

  • Qiang Ye
    Department of Mathematics, Departments of Computer Science and Internal Medicine University of Kentucky, Lexington, Kentucky 40506-0027.
  • Hening Yang
    School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Bomiao Lin
    Department of Radiology, ZhuJiang Hospital of Southern Medical University, Guangzhou, China.
  • Menghong Wang
    Department of Radiology, The Third Affiliated Hospital of Southern Medical University (Academy of Orthopedics, Guangdong Province), Guangzhou, Guangdong, China.
  • Liwen Song
    Department of Radiology, The Third Affiliated Hospital of Southern Medical University (Academy of Orthopedics, Guangdong Province), Guangzhou, Guangdong, China.
  • Zhuoyao Xie
    Department of Radiology, The Third Affiliated Hospital of Southern Medical University (Academy of Orthopedics, Guangdong Province), Guangzhou, Guangdong, China.
  • Zixiao Lu
    School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China.
  • Qianjin Feng
    Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China. Electronic address: qianjinfeng08@gmail.com.
  • Yinghua Zhao
    Department of Radiology, The Third Affiliated Hospital of Southern Medical University (Academy of Orthopedics, Guangdong Province), Guangzhou, Guangdong, China. zyh7258957@163.com.

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