Brain tumor image segmentation method based on deep learning and weight space integration

Abstract

The invention discloses a brain tumor image segmentation method based on deep learning and weight space integration, comprising the following steps: S1, collecting multimodal MRI images of brain tumors, and performing preprocessing operations on the collected multimodal MRI images; S2 , constructing the first network model and the second network model; S3, inputting the preprocessed multimodal MRI image into the second network model, passing through the weight space, and updating the average weight; training it, and averaging the trained weights The value is stored in the first network model; S4. Input the multimodal MRI image to be tested into the first network model, and output the segmentation result of the brain tumor image. The segmentation method in the present invention is conducive to improving the accuracy and reliability of brain tumor segmentation results. The parallel network can obtain positioning information while segmenting lesions, and at the same time integrate into the method of weight space set, which improves the efficiency and accuracy of brain tumor segmentation. .

Description

technical field [0001] The invention belongs to the technical field of medical image segmentation, and in particular relates to a brain tumor image segmentation method based on deep learning and weight space integration. Background technique [0002] Medical image segmentation is a key technology in image analysis and processing. Separating relevant tissues of interest according to the similarity and specificity of the image area is of great significance to the clinical diagnosis and treatment process and is the main premise of all follow-up work. , the quality of the segmentation effect will directly affect the smooth progress of the information processing work. Medical image segmentation of brain tumors is an important branch in the field of image segmentation. Brain tumor segmentation technology plays an important role in the clinical diagnosis and treatment of brain tumors. Through the segmentation results of brain tumors, doctors can measure tumor Size and location, su...

AI Technical Summary

Problems solved by technology

[0006] In view of the above-mentioned deficiencies in the prior art, the brain tumor image segmentation method based on deep learning and weight space integration provided by the present invention solves the problem of rough image segmentation and unbalanced categories in the prior art.

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