A neural network-based cerebral ischemia risk prediction platform

Abstract

The invention relates to a neural network-based cerebral ischemia risk estimation platform, which comprehensively considers carotid plaque data and brain magnetic resonance images. ) and obviously abnormal plaques (high risk), leaving carotid plaques that are not easy to judge without obvious stenosis, and then use brain magnetic resonance images to break the conventional perception of carotid plaques themselves. Research to explore the relationship between plaque and brain structure, based on neural network modules, can predict carotid plaques from the initial changes of the brain, and estimate the level of cerebral ischemia risk, which can be used for the assessment of cerebral ischemia risk. It is used for the prediction and prevention of acute stroke, chronic cerebral ischemia, vascular dementia, etc. It is used for clinical prediction. It has a very positive effect on prevention before it occurs. It can improve the accuracy of diagnosis and save the disease to a greater extent and in a timely manner. suffer from life.

Description

technical field [0001] The invention relates to an image analysis technology, in particular to a cerebral ischemia risk estimation platform. Background technique [0002] Stroke, heart disease, and malignant tumors together constitute the three leading causes of death in most countries. Among them, stroke has surpassed malignant tumor as the leading cause of death in my country. In particular, ischemic stroke accounts for 60%-80% of all strokes. Therefore, early prevention of stroke and stroke-related complications, especially ischemic stroke, vascular dementia, etc., is extremely necessary. [0003] Most of the previous studies have focused on the brain function changes in patients with moderate to severe carotid artery stenosis, and less attention has been paid to patients with carotid artery disease without mild stenosis or plaque. However, more and more evidences show that the amygdala and hypothalamus are important brain structures that regulate the inflammatory resp...

AI Technical Summary

Problems solved by technology

Conversely, with different degrees of carotid atherosclerosis, or even in the early stages of carotid plaque formation, the default brain network (DMN) begins to accept negative feedback regulation, and symptoms such as headache, dizziness, and insomnia gradually appear clinically, but they cannot be detected by existing imaging studies. Means Detection Analysis

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