Hip replacement post-operation image evaluation method and system based on deep learning

Abstract

The invention provides an evaluation method and system for images after hip replacement based on deep learning, relates to the technical field of medicine, and can accurately evaluate the postoperative condition of a patient subjected to total hip replacement surgery, and the method comprises the following steps: obtaining a hip joint image of the patient subjected to the hip replacement surgery; recognizing key point positions and target areas in the hip joint image based on a deep learning target recognition network; according to the key point position and the target area, the leg length difference, the eccentric distance and the femoral prosthesis index of the patient are determined; according to the leg length difference of the two legs, the eccentric distance and the femoral prosthesis index, the accuracy of femoral prosthesis position installation of the patient is evaluated. The system executes the method. According to the method, based on the hip joint image of the patient after the hip joint replacement operation, the leg length difference, the eccentric distance and the femoral prosthesis index of the patient after the hip joint replacement operation are calculated, so that the recovery condition of the patient after the hip joint replacement operation is accurately evaluated.

Description

technical field [0001] The invention relates to the field of medical technology, and in particular, to a deep learning-based image evaluation method and system after hip replacement. Background technique [0002] Postoperative evaluation of hip replacement surgery in the medical field plays a very important role in the success rate of the operation, so it is very important to provide an accurate postoperative evaluation. [0003] At present, the main preoperative assessment method is manual measurement through various tools, which is inefficient and cannot be guaranteed to be accurate. Therefore, it is urgent to provide a more convenient and accurate postoperative assessment method. SUMMARY OF THE INVENTION [0004] The method and system for evaluating images after hip replacement based on deep learning provided by the present invention are used for the above problems existing in the prior art. Postoperative leg length difference, eccentricity, and femoral prosthesis indi...

AI Technical Summary

Problems solved by technology

[0003] At present, the main preoperative evaluation method is manual measurement through various tools, which is inefficient and cannot guarantee accuracy. Therefore, it is urgent to provide a more convenient and accurate postoperative evaluation method.

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