A brain tumor medical image segmentation method based on deep learning

Abstract

The invention relates to the technical field of brain tumor medical image segmentation, in particular to a brain tumor medical image segmentation method based on deep learning, which comprises the steps of training a segmentation model, receiving the to-be-segmented brain tumor medical image data information, performing the segmentation processing on the received to-be-segmented brain tumor medical image data information, and outputting a segmentation result. The brain tumor medical image segmentation system based on deep learning comprises a segmentation model training module, a brain tumor medical image receiving module, a brain tumor medical image segmentation processing module and a segmentation result output module. According to the medical brain tumor image segmentation method basedon deep learning, deep learning training is carried out on the segmentation model, the segmentation model trained through deep learning carries out segmentation processing on the received medical brain tumor image data information to be segmented, the segmentation result is accurate, and the problem that a traditional manual segmentation method is time-consuming and labor-consuming is solved.

Description

technical field [0001] The present invention relates to the technical field of brain tumor medical image segmentation, in particular to a method, system and electronic equipment for brain tumor medical image segmentation based on deep learning. Background technique [0002] Brain tumor medical image segmentation technology is a key technology in brain tumor medical image processing and analysis. Brain tumor medical image segmentation is a process of separating relevant structures (or regions of interest) in the image according to the similarity within the region and the difference between regions. The early image segmentation was completely done manually. The complete manual segmentation method is that medical experts manually delineate the boundaries on hundreds of slice images, and conceive the three-dimensional structure of the lesion and its surrounding tissues and Spatial relationships, and use this as the basis for developing a treatment plan. [0003] The traditiona...

AI Technical Summary

Problems solved by technology

[0003] The traditional manual segmentation method is time-consuming and labor-intensive. At present, with the development of digital medical technology, it is necessary to study an automatic segmentation method for brain tumor medical images.

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