Hip joint image processing method based on deep learning and computing equipment

Abstract

The invention discloses a hip joint image processing method based on deep learning, and the method is suitable for being executed in computing equipment, and comprises the steps: obtaining hip joint information corresponding to a hip joint to be subjected to an operation, and enabling the hip joint information to comprise a hip joint image of the hip joint and operation information related to theoperation; inputting the hip joint image into a hip joint segmentation model assembly determined from the operation information, and obtaining a three-dimensional skeleton model image only comprisinga skeleton; labelling the positions of key points in a three-dimensional skeleton model image to generate a labeled skeleton image with labeled data. By the adoption of the three-dimensional measurement system and method, three-dimensional measurement data with high accuracy can be provided for prosthesis replacement before a total hip replacement operation is conducted.

Description

Technical field [0001] The present invention relates to the field of image processing technology, in particular to a hip joint image processing method and computing equipment based on deep learning. Background technique [0002] With the rapid development of digital medicine, the application of digital technology in surgical operations is becoming more and more important. Digital surgical planning overcomes the visual limitations of surgeons, making data measurement more accurate, diagnosis more accurate, and surgery more accurate and efficient. . [0003] For orthopedic surgery (for example, hip replacement surgery), traditional methods use a combination of X-ray films and prosthetic templates to plan and formulate surgical plans before surgery. The traditional planning method uses the prosthesis template to compare on the X-ray film, because the X-ray and the template scale are not uniform, the planning result cannot accurately predict the actual size of the prosthesis during th...

AI Technical Summary

Problems solved by technology

The traditional planning method uses the prosthesis template to compare on the X-ray film, because the scale of the X-ray and the template is not uniform, the planning result cannot accurately predict the actual size of the prosthesis used during the operation, and the traditional method cannot display three-dimensional parameters and cannot evaluate the prosthesis For the spatial location of the placement, the surgeon uses the traditional method for preoperative planning, which takes a long time, and there are often situations where the preoperative planning information does not match the actual size, model, and spatial location information of the prosthesis.

Therefore, the traditional planning method takes a long time to plan, the results are inaccurate, and information such as three-dimensional parameters and spatial position angles cannot be displayed, and the difficulty of surgery cannot be effectively reduced. Sometimes, wrong information is even provided to clinicians, which increases the risk of surgery.

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