Focus analysis method and device based on medical images

Abstract

The embodiment of the invention provides a focus analysis method and device based on medical images, electronic equipment and a computer readable storage medium. The invention solves the problem thatfocus analysis in the medical image is not comprehensive and not accurate enough in the prior art. The focus analysis method comprises the following steps: extracting focus characterization data basedon medical image data; extracting focus feature information based on the focus representation data; inputting the lesion feature information into a first machine learning model to obtain a first lesion feature vector; inputting the medical image data and the focus representation data into a second machine learning model to obtain a second focus feature vector; combining the first lesion feature vector and the second lesion feature vector to obtain a fusion feature vector corresponding to the lesion; and obtaining an analysis result of the focus according to the fusion feature vector.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular to a method, device, electronic device and computer-readable storage medium for lesion analysis based on medical images. Background technique [0002] Pneumonia is a common respiratory inflammatory disease, mainly refers to lung infection caused by bacteria, viruses, etc. In early pneumonia, the lesion area shown on CT (Computed Tomography) images is small and not obvious. When doctors observe , it takes a lot of time to find the corresponding lesions. Recently, the novel coronavirus pneumonia is rampant, and CT images, as one of the important indicators for judging the novel coronavirus pneumonia, have greatly increased the workload of radiologists. [0003] At present, in the prior art, neural networks are used to detect lesions in medical images, extract feature information of lesions, obtain lesion areas in the form of marked frames, and identify and mark les...

AI Technical Summary

Problems solved by technology

[0003] At present, in the prior art, neural networks are used to detect lesions in medical images, extract feature information of lesions, obtain lesion areas in the form of marked frames, and identify and mark lesions. Due to the use of marked frames, the specific shape of lesions It cannot be expressed, only the location of the lesion can be determined, and a more comprehensive analysis of the lesion cannot be performed

Using artificial intelligence network to identify and analyze the characteristics of lesions in medical images, and compare them with the characteristics of lesions in medical images in the database, and identify lesions according to the comparison results. Due to the variety of lesions, only the lesions are compared with the lesions in the database , instead of analyzing the lesion itself, which makes the identification result inaccurate

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