Toward automatic quantification of knee osteoarthritis severity using improved Faster R-CNN.

Journal: International journal of computer assisted radiology and surgery
Published Date: Jan 14, 2020

Abstract

PURPOSE: Knee osteoarthritis (OA) is a common disease that impairs knee function and causes pain. Radiologists usually review knee X-ray images and grade the severity of the impairments according to the Kellgren-Lawrence grading scheme. However, this approach becomes inefficient in hospitals with high throughput as it is time-consuming, tedious and also subjective. This paper introduces a model for automatic diagnosis of knee OA based on an end-to-end deep learning method.

Authors

  • Bin Liu
    Department of Endocrinology, the First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Department of Endocrinology, Neijiang First People's Hospital, Chongqing, China.
  • Jianxu Luo
    School of Information Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China. jxluo@ecust.edu.cn.
  • Huan Huang
    School of Information Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China.

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