Osteotomy positioning method based on AI machine learning

Through the osteotomy and positioning method based on AI machine learning, the problem that the knee joint navigation system cannot effectively limit the internal and external rotation of the implant during knee arthroplasty surgery is solved, and the high accuracy and safety of the surgery are achieved, ensuring the functional recovery of the knee joint and the correctness of the force line.

CN119867871AInactive Publication Date: 2025-04-25BEIJING NATON INST OF MEDICAL TECH CO LTD
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Patent Information

Application Number
CN202510356624.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-25
Publication Date
2025-04-25
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

In existing knee arthroplasty surgery, the knee navigation system cannot effectively limit the internal and external rotation of the knee implant, resulting in a deviation of the force line, which may lead to excessive wear of the joint, uneven load distribution, pain, joint dysfunction, and even failure of the surgery.

Method used

Using an osteotomy positioning method based on AI machine learning, the osteotomy positioning method is reconstructed and generated by preoperative three-dimensional anatomical model to measure and verify the lower limb force line data in real time, the navigation system is used to provide osteotomy feedback, adjust the surgical operation, and adjust the osteotomy position and angle through iterative optimization algorithm to ensure the correctness of the force line.

Benefits of technology

It improves the accuracy and safety of the surgery, ensures the functional recovery of the knee joint and the correctness of the force line, extends the service life of the prosthesis, and reduces postoperative complications.

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Abstract

The invention discloses an osteotomy positioning method based on AI machine learning, and relates to the technical field of orthopedic surgery. The osteotomy positioning method based on AI machine learning specifically comprises the following steps: S1, preoperative preparation and planning; s2, performing intraoperative operation and navigation; s3, external rotation positioning and osteotomy plate installation; s4, verifying a four-in-one positioning point; s5, performing osteotomy operation and verification; a real medical record reconstruction model is provided through a matched preoperative planning system, and an optimal surgical scheme is planned according to the model; reconstructing a three-dimensional anatomical model on the basis of CT data of a real patient, and generating matched osteotomy data by selecting a bony mark point of the three-dimensional model; on the basis of AI machine learning, after an osteotomy scheme is generated, an operator can further adjust the osteotomy scheme according to a personal operation concept, and a finally determined operation scheme is generated; a surgeon can be helped to adjust the alignment of the knee joint and the alignment of the prosthesis so as to ensure the functional recovery of the postoperative knee joint and the correctness of the force line of a patient, thereby prolonging the service life of the prosthesis and reducing postoperative complications.
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