Cerebral apoplexy typing method and device based on vascular image completion

Abstract

The invention relates to a cerebral apoplexy typing method and device based on vascular image completion, and the method comprises the steps: carrying out the image processing of a first target image of an object brain, and obtaining cerebral infarction focus information; performing image processing on the second target image of the brain of the object to obtain a blood vessel reconstruction result; performing blood vessel fracture state detection on the blood vessel reconstruction result to obtain a to-be-complemented interruption point; performing blood vessel completion at the interruption point to be completed to obtain a completed blood vessel reconstruction result; obtaining brain vasculopathy information according to the complemented vascular reconstruction result; and according to the cerebral infarction lesion information and the brain vasculopathy information, obtaining a cerebral apoplexy typing result of the object. According to the embodiment of the invention, the blood vessel occlusion condition can be effectively counted, and the blood vessel occlusion position is automatically complemented to be in a normal through state under the condition that the blood vessel fracture form exists in the obtained blood vessel reconstruction result, so that the accuracy and efficiency of cerebral apoplexy typing result recognition are improved.

Description

technical field [0001] The present disclosure relates to the technical field of image processing, in particular to a stroke classification method and device based on vascular image complementation. Background technique [0002] Currently, there are mainly two classification methods for ischemic stroke: clinical symptom classification and etiological classification. When judging the classification of ischemic stroke, primary hospitals are still using manual judgment to diagnose the degree of vascular stenosis and occlusion due to the constraints of medical equipment conditions and physician team strength, while general automatic analysis software or The situation of occlusion cannot be judged and processed, or the occlusion cannot be judged and processed, or the degree of stenosis cannot be effectively judged. Therefore, the identification of ischemic stroke has problems of low accuracy, low efficiency, and non-objectiveness. Contents of the invention [0003] According to...

AI Technical Summary

Problems solved by technology

When judging the classification of ischemic stroke, primary hospitals are still using manual judgment to diagnose the degree of vascular stenosis and occlusion due to the constraints of medical equipment conditions and physician team strength, while general automatic analysis software or Unable to judge and deal with occlusion, or unable to judge and deal with occlusion, or unable to complete the effective judgment of the degree of stenosis, so the identification of ischemic stroke has problems of low accuracy, low efficiency, and non-objective

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