Title:
DEEP LEARNING-BASED KNEE JOINT FEMORAL REPLACEMENT POSTOPERATIVE EVALUATION SYSTEM
Document Type and Number:
WIPO Patent Application WO/2023/165260
Kind Code:
A1
Abstract:
The present application provides a deep learning-based knee joint femoral replacement postoperative evaluation system, comprising an acquisition module, configured to acquire a postoperative knee joint image; an identification module, configured to input the postoperative knee joint image into a deep learning-based identification model, so as to obtain contour areas of a femur and of a femoral prosthesis in the postoperative knee joint image output by the identification model; a calculation module, configured to obtain a key axis according to the contour areas of the femur and of the femoral prosthesis, and obtain an angle parameter of the femoral prosthesis according to the key axis; and an evaluation module, configured to obtain a postoperative evaluation result according to the angle parameter of the femoral prosthesis. The present application may automatically measure the angle parameter of the postoperative knee joint prosthesis, so as to accurately evaluate a surgery result, and save a large quantity of time, energy and financial resources.
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Inventors:
ZHANG YILING (CN)
LIU XINGYU (CN)
LIU XINGYU (CN)
Application Number:
PCT/CN2023/070789
Publication Date:
September 07, 2023
Filing Date:
January 05, 2023
Export Citation:
Assignee:
LONGWOOD VALLEY MEDTECH (CN)
ZHANG YILING (CN)
ZHANG YILING (CN)
International Classes:
G06T7/00
Foreign References:
| CN114612400A | 2022-06-10 | |||
| CN111768400A | 2020-10-13 | |||
| CN113017829A | 2021-06-25 | |||
| CN1452946A | 2003-11-05 |
Other References:
88: "Postoperative Imaging Evaluation of Total Knee Arthroplasty PPT", DOCIN, pages 1 - 32, XP009549249, Retrieved from the Internet
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