Image data-based segmentation method, device and equipment

Abstract

The embodiment of the invention discloses a segmentation method, device and equipment based on image data. The method comprises the following steps that CTA image data to be processed is acquired; the to-be-processed CTA image data are input into a segmentation model, the to-be-processed CTA image data are segmented, a three-segmentation result is obtained, the segmentation model is a three-segmentation model obtained in advance through neural network training on the basis of a semi-automatic labeling method, the three segmentation results are a bone tissue segmentation result, a blood vessel segmentation result and a calcified tissue segmentation result of the to-be-processed CTA image data. By adopting the segmentation method provided by the specification, the segmentation of bone tissues, calcified tissues and blood vessels can be automatically realized, the analysis time is greatly saved, and the accuracy is relatively high.

Description

technical field [0001] This specification relates to the field of medical imaging and computer technology, in particular to a segmentation method, device and equipment based on image data. Background technique [0002] CTA (computed tomography angiography) image data has important clinical applications and can be used as an auxiliary diagnostic means for the clinical treatment of intracranial aneurysms. Since the bone tissue in brain imaging will affect the clinical diagnosis results, in order to achieve better diagnostic results and reduce diagnostic errors, it is often necessary to remove bone tissue in brain imaging data. [0003] In the prior art, for bone removal of CTA image data, two sets of images are generally used, and bone tissue is removed through differential processing. Specifically, using non-contrast CT image data (NCCT) and CTA image data, wherein, the NCCT image is an image that does not need to be injected with a contrast agent, and the CTA image is an im...

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