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
Engineering ›› 2021, Vol. 7 ›› Issue (6) : 881 -888.
Multi-View Point-Based Registration for Native Knee Kinematics Measurement with Feature Transfer Learning
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.
2D–3D registration / Machine learning / Domain adaption / Point correspondence
()
/
| 〈 |
|
〉 |
PDF
(1177KB)
