Ultrasound diagnosis method of knee joint disorders based on deep learning multi-channel and image embedding method

Abstract

The invention discloses a method for ultrasonic diagnosis of knee joint disease based on deep learning multi-channel and image embedding method, which includes the following steps: using snake algorithm to preprocess the effusion area in the knee joint ultrasonic image, and then input it into the defined Semantic segmentation is realized in the network model of Resnet; On the basis of Resnet network structure, utilize the image embedding method of secondary training to train the knee joint ultrasound image in data set, finally utilize the experiment of segmentation network and classification network to verify; The present invention adopts The idea of ​​multi-channel superposition and image embedding method is used to segment and train the knee joint ultrasound images, and the disease category can be distinguished according to whether the effusion area is accompanied by synovial thickening in the ultrasound images of different knee joint diseases, avoiding the problem of knee joint ultrasound images. The judgment depends entirely on the doctor's naked eyes and personal judgment, eliminating the problems of subjectivity and human error. The entire segmentation and classification recognition method is simple and efficient, and the diagnosis is accurate.

Description

technical field [0001] The invention relates to the technical field of machine vision, in particular to an ultrasonic diagnosis method for knee joint disorders based on deep learning multi-channel and image embedding method. Background technique [0002] The knee joint is the most complex joint in the human body, and people of all ages are susceptible to infection or injury. Common knee-related diseases include synovitis, synovial thickening, and cysts. Medical images are a common and important method for knee joint diagnosis at present. The liquid area of ​​the lesion appears as a darker black area in the image. Doctors use this area as the main basis for judgment. At the same time, the accuracy of the area demarcation also affects The doctor's correct diagnosis. At present, the diagnosis of common diseases of the knee completely depends on the doctor's naked eyes and personal judgment, which wastes a lot of manpower and material resources, and has certain subjectivity and...

AI Technical Summary

Problems solved by technology

At present, most of the processing of knee ultrasound images still stays on the traditional algorithm. The deep learning algorithm, which is widely used in image processing in various fields, has not been effectively applied to ultrasound images, so its application and knee ultrasound Images are necessary and have important application context

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