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Total knee arthroplasty prosthesis model prediction method

A technology of total knee joint replacement and prediction method, applied in neural learning methods, biological neural network models, instruments, etc., to achieve the effect of low cost

Active Publication Date: 2020-02-11
PEKING UNIV +1
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problem that the existing prosthesis selection relies too much on the doctor's personal experience, the purpose of the present invention is to provide a prosthesis model prediction system framework and a prosthesis model classification method based on deep learning

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  • Total knee arthroplasty prosthesis model prediction method
  • Total knee arthroplasty prosthesis model prediction method

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Embodiment 1

[0035] The structure of the prosthesis type prediction system for total knee arthroplasty is as follows: figure 1 Shown:

[0036] 1. Data collection and screening.

[0037] The basic data (gender, height, weight) and preoperative knee X-ray films of patients undergoing total knee arthroplasty in a provincial tertiary hospital from 2014 to 2018 were collected. Convolutional neural network model with strong precision and generalization, so the present invention is based on transfer learning, first trains on a similar large data set, and then migrates back to the original data set to fine-tune the model structure and parameters.

[0038] 1) Select the selected data according to the aforementioned criteria for subsequent processing.

[0039] 2) For the data that meets the exclusion criteria, it is not used for the incremental training of the subsequent model, but the model can be used to predict it and provide surgical advice for doctors.

[0040] 2. Data preprocessing.

[004...

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Abstract

The invention discloses a total knee arthroplasty prosthesis model prediction method. The model comprises the steps that X-ray films of patient' knee joints before surgery and basic information of a patient are collected, wherein the X-ray films meet selection standards; the collected X-ray films and the basic information of the patient are preprocessed; and the pre-processed pictures and the basic information of the patient are used as features and input to a prosthesis model classifier trained based on a deep learning technology to acquire the use probability of each type of prosthesis in the surgery. According to the invention, the required prosthesis model can be efficiently and accurately predicted, and the detection accuracy rate can reach more than 84%; the accuracy rate reaches thesame level as the accuracy rate of preoperative prediction of experienced experts using CT and X-ray films; and the method provided by the invention only needs to use the X-ray films and the basic information of the patient, and has lower cost.

Description

technical field [0001] The invention belongs to the field of artificial intelligence medical image processing, and in particular relates to the design of a prosthesis type prediction system for total knee arthroplasty and a prosthesis type prediction method based on the system. Background technique [0002] Total knee arthroplasty (Total Knee Arthroplasty, TKA) is an effective method for the treatment of severe knee osteoinflammation and other diseases. While obtaining good clinical efficacy and reliable prosthesis survival rate, it also faces a series of postoperative complications. It affects the clinical curative effect of patients, and even requires revision surgery again, which increases the pain and medical burden of patients. According to different studies, the satisfaction rate of patients after total knee arthroplasty is only around 80%. [0003] Accurate prosthesis matching is considered to be one of the important factors to reduce complications such as postoperat...

Claims

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Application Information

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IPC IPC(8): G16H30/40G16H50/20G06K9/62G06N3/04G06N3/08
CPCG16H30/40G16H50/20G06N3/08G06N3/045G06F18/241
Inventor 岳宇王鑫光赵旻暐田华曹志崴高翘楚李斗
Owner PEKING UNIV
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