Method for Obtaining Volume of Interest in Four-Dimensional Cardiac Image

Abstract

The invention relates to a method for obtaining the volume of interest of a four-dimensional heart image, which belongs to the technical field of image processing. The method comprises the following steps that volume data of a tissue structure is read, voxelization treatment is performed, and regional projection is selected to an interactive polygon through a set of triangular patches, so as to obtain myocardial four-dimensional visualization data based on the volume data; then precise extraction and grid expansion are performed on a selected region in a gridding projection surface, so as to obtain all surface elements involved in a region of interest; and finally, octree encoding and consistency extraction are performed to obtain a voxel set of any sequential image, thereby realizing four-dimensional visualization data of a cardiovascular system on the basis of the volume data. By using the method, a local tissue volume data set corresponding to a contour of the extracted heart region of interest can be automatically obtained, and finally, local extraction and visualization of the four-dimensional heart image are realized. Because the space occupied by the extracted local volume data set is obviously less than the space occupied by the integral volume data set, compared with the space occupied by an image stack before extraction, the space occupied by the extracted image stack is greatly reduced, and therefore, the time consumed by four-dimensional visualization is greatly reduced.

Description

technical field [0001] The present invention relates to a method in the technical field of medical image processing, in particular to a method for extracting a heart volume of interest (VOI, volume of interest) by drawing a polygonal region of interest on the surface of heart volume data. Background technique [0002] The World Heart Federation announced that the number of deaths due to heart disease accounts for one-third of the total number of deaths worldwide every year. Therefore, the early prevention and treatment of heart disease becomes very important. So far, there have been many segmentation algorithms for some anatomical tissues in the human heart, the most common ones are the segmentation of tissue structures such as coronary arteries, atria, and ventricles. Since the segmentation objects of these segmentation algorithms are targeted, they cannot be segmented in a unified way. Because the tissue structure of the heart is very complex, including atria, ventricles...

AI Technical Summary

Problems solved by technology

For example, binary space segmentation BSP (BinarySpacePartitioning) has become the leading space segmentation technology due to its high efficiency and recursion, but the disadvantage of BSP is that it is very complicated to choose a surface that divides the polygon in the space into a pair of equal subsets. , because there are infinitely many faces that can be selected

So picking the most suitable face in the set is difficult to implement

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