Medical image processing method, device, equipment and system

Abstract

The invention belongs to the technical field of image processing, discloses a medical image processing method, device, equipment and system. The method comprises steps of obtaining a lesion area blockin the original medical image and a lesion contour in the lesion area block through the segmentation model, recognizing lesion grade indication information of the lesion area block through the recognition model, synthesizing the lesion grade indication information of the lesion area block and the lesion contour on the original medical image, and outputting a lesion diagnosis image. Thus, the accurate boundary of the lesion contour can be determined, the lesion position is accurately positioned, the false alarm rate of lesion recognition is reduced, and accurate judgment of lesion recognitionis achieved.

Description

technical field [0001] The present application relates to the technical field of image processing, and in particular to a medical image processing method, device, device and system. Background technique [0002] With the development of computer technology, computer technology is gradually applied to the analysis of medical images (eg, mammography images) to assist doctors in medical diagnosis. For example, the terminal device can judge whether a patient's breast has a lesion according to the mammography image through computer technology. In this way, doctors can conduct further diagnostic analysis based on the output results, and then formulate corresponding treatment plans, which improves the accuracy and efficiency of medical diagnosis. [0003] Under the existing technology, when performing disease analysis through medical images, the following methods are usually adopted: [0004] Use wavelet transform and genetic algorithm to segment abnormal areas of medical images, ...

AI Technical Summary

Problems solved by technology

[0005] However, on the one hand, due to the diversity of tumors, it is difficult to set a set threshold that can be widely used, which makes the screening error of the lesion area large, and it is impossible to accurately locate the lesion outline

On the other hand, a large number of professional and technical personnel are required for manual identification, and the efficiency of disease diagnosis is low

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