Method for obtaining the coronary artery vasomotion information

Abstract

A method for acquiring the motion information of coronary artery, which belongs to the field of medical detection technology, is used for solving the problem in acquiring the motion information of heart. The technical scheme is that a 3D motion estimation method based on elastic registration is adopted after achieving 3D reconstruction of branch skeleton of main blood vessels at each moment in X-ray coronary artery angiogram sequences; the motion of blood skeleton is transformed to be matched with skeleton lines at continuous time moments; the motion vector and the motion trajectory of each blood skeleton point in cardiac cycle are calculated; and the motion information including global and the local motion parameters of the coronary artery in the cardiac cycle is extracted according to the estimated motion vector of each blood skeleton in the image sequence. The method has the advantages of high accuracy in extracting the motion information of blood vessels, convenient operation and high work efficiency.

Description

technical field [0001] The invention relates to a method for extracting blood vessel-related motion information from digital X-ray coronary angiography image sequences covering one or more cardiac cycles, and belongs to the technical field of medical detection. Background technique [0002] The coronary artery is an important blood vessel that supplies the heart. It is located on the epicardial surface and moves rhythmically with the myocardium during the cardiac cycle. Therefore, the movement of the coronary artery can reflect the movement of the heart itself. X-ray coronary angiography is currently the main basis for the diagnosis and treatment of coronary heart disease internationally recognized. The use of angiographic images can not only detect the location and degree of ischemic injury (vascular stenosis), compared with one or two static images of the same scene, the image sequence can provide richer information, that is, it implies Dynamic information such as vascula...

AI Technical Summary

Problems solved by technology

In the former case, the signal-to-noise ratio of clinically collected coronary angiography images is generally low, and different blood vessels often overlap each other in the image, so it is very difficult to accurately extract the blood vessel structure from the image, and often requires a lot of manual participation by the operator , the existing fully automatic algorithm cannot guarantee success for any image; the latter generally uses the epipolar constraints in computer vision as the basis for matching, and the accuracy of epipolar line matching depends on the accuracy of the geometric transformation matrix of the imaging system. Moreover, errors introduced by two-dimensional processing may also lead to wrong matching of pixels.

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