Method for extracting center line of coronary artery blood vessel

Abstract

The invention discloses a method for extracting a center line of a coronary artery blood vessel. The method comprises the steps that S1, coronary artery tree data and aorta data are input; S2, a starting point of a coronary artery tree and ending points of all branch blood vessels are automatically extracted; S3, a Marching Cubes algorithm is used to make the coronary artery tree data into grid model data; S4, Delaunay triangulation processing is performed on all points on a grid, and a three-dimensional Voronoi diagram is generated; S5, the starting point and the ending points of all the branch blood vessels are located on the Voronoi diagram, and the shortest path between the starting point and the ending points is calculated to obtain several corresponding curves; and S6, isometric filtering is performed on the obtained curves, and complete center line data is formed. The method has the advantages that the starting point and the ending points of the coronary artery blood vessel areautomatically acquired, and the accuracy of the center line is guaranteed; and the powerful processing capability of a computer is fully utilized, the step of acquiring the starting point and the ending points through a manual interaction mode is omitted, and the efficiency of doctor diagnosis is greatly improved.

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.

Images