SYNTAX automatic scoring method based on coronary angiogram image segmentation

Abstract

An SYNTAX automatic scoring method based on coronary angiogram image segmentation segments and extracts a coronary arterial tree and central line based on coronary angiogram images of a patient and employs a blood vessel side branch separation, reconnection and K main curve method, and generates a binary image of the coronary arterial tree The blood vessel segment numbers are automatically matched based on the SYNTAX scoring standard by employing a central line direction tracking method, and coronary artery pathological changes and adverse characteristics are identified and scored by selecting a coronary left (right) advantageous type in combination with the width attenuation degree of the cross section of the blood vessel and the curvature change of the center line, and the scores are calculated to give a reasonable score result to allow a doctor to employ optimal operation scheme. The method overcomes the problems of great computation amount, tedious calculating steps, complex scoring standard and long calculating time of artificial calculating SYNTAX scoring in conventional clinics.

Description

technical field [0001] The invention relates to the segmentation and extraction of vascular trees in coronary angiographic images, and belongs to the technical field of clinical medical image processing. Background technique [0002] Cardiovascular disease, as one of the high-incidence and fatal diseases that endanger human health, is usually caused by narrowing and blockage of coronary arteries. Coronary angiography is an important method for diagnosing heart disease and the "gold standard" for clinical diagnosis of vascular disease. Although the injection of contrast agent will make the brightness of blood vessels in the contrast image higher than that of other tissues such as the heart, the gray value of the image is inconsistent due to the uneven distribution of contrast agent and the influence of environmental noise in the imaging process; There are many branches, the shape is complex, and the gray contrast of the distal blood vessels is very low, which greatly affects...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the problems of complex scoring procedures, large amount of calculation, long time-consuming and not yet combined with coronary angiography image segmentation technology in clinical SYNTAX manual scoring, the present invention proposes a SYNTAX automatic scoring system based on coronary angiography image segmentation The method comprises: a coronary angiography image reading and display module, a coronary angiography image vessel segmentation module (including a coronary angiography image vessel enhancement module, a coronary angiography image vessel and its branch identification module, a vessel centerline extraction module, and a vessel diameter calculation module), SYNTAX automatic scoring module (including coronary tree segment labeling module, lesion site and lesion feature recognition module, and SYNTAX automatic scoring module)

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