Engineering (Jun 2021)

Multi-View Point-Based Registration for Native Knee Kinematics Measurement with Feature Transfer Learning

  • Cong Wang,
  • Shuaining Xie,
  • Kang Li,
  • Chongyang Wang,
  • Xudong Liu,
  • Liang Zhao,
  • Tsung-Yuan Tsai

Journal volume & issue
Vol. 7, no. 6
pp. 881 – 888

Abstract

Read online

Deep-learning methods provide a promising approach for measuring in-vivo knee joint motion from fast registration of two-dimensional (2D) to three-dimensional (3D) data with a broad range of capture. However, if there are insufficient data for training, the data-driven approach will fail. We propose a feature-based transfer-learning method to extract features from fluoroscopic images. With three subjects and fewer than 100 pairs of real fluoroscopic images, we achieved a mean registration success rate of up to 40%. The proposed method provides a promising solution, using a learning-based registration method when only a limited number of real fluoroscopic images is available.

Keywords