A method for extracting coronary artery centerline

Abstract

The invention discloses a method for extracting the centerline of coronary artery blood vessels, comprising the following steps: Step S1: input the data of coronary artery tree and aorta; Step S2: automatically extract the starting point of coronary artery tree and the end of all branch vessels point; step S3: use the Marching Cubes algorithm to generate grid model data from the coronary tree data; step S4: carry out Delaunay triangulation processing to all points on the grid and generate a three-dimensional Voronol diagram; step S5: on the Voronoi diagram Locate the start point and the end points of all branch vessels, and calculate the shortest path between the start point and the end point to obtain several corresponding curves; step S6: perform equidistant filtering on the obtained curves to form a complete centerline data; its advantage is to automatically obtain the start point and end point of the coronary artery, which ensures the accuracy of the centerline and makes full use of the powerful processing power of the computer, eliminating the steps of obtaining the start point and end point by manual interaction, which greatly Improve the efficiency of doctors' diagnosis.

Description

technical field [0001] The invention belongs to the field of medical blood vessel image processing, and in particular relates to a method for extracting the center line of a coronary artery. Background technique [0002] With the development and progress of modern science and technology, the application of medical imaging technology is becoming more and more extensive, and it is favored by more and more doctors and accepted by more and more patients. Contrast images are often used by doctors as a reference for the diagnosis of clinical diseases and formulation of treatment plans. Due to the influence and constraints of doctors' subjective factors, it is not enough to analyze and judge the contrast images only by doctors' clinical experience and vision. It has become an inevitable trend to use the efficiency and accuracy of computers to quantitatively analyze contrast images. In clinical practice, doctors hope to obtain quantitative analysis results by analyzing blood vessel...

AI Technical Summary

Problems solved by technology

The disadvantages are: the iterative calculation process is time-consuming, and it is easily affected by the image quality, and the transition effect at the bifurcation point is poor

The disadvantages are: this method is based on the local method, and the global information is not considered in the tracking process, so sometimes the obtained centerline will be incomplete. Large or branched locations, centerline extraction is prone to errors

The disadvantage is that the generated centerline is not accurately located in the center of the object, but tends to be close to the inner wall of the object, so it often requires later adjustments, and manual interaction is required to specify the start point and end point

This method is more popular, but the disadvantage is that the start and end points of the centerline need to be specified

[0007] All of the above methods need to specify the start point and end point through interaction before generating the centerline. All blood vessels cannot be fully identified automatically, and the operations of each doctor are not uniform, resulting in diversity of results.

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