Three-dimensional brain blood vessel model construction method based on tree structure

Abstract

The invention discloses a three-dimensional brain blood vessel model construction method based on a tree structure. The method includes the following steps: firstly, acquiring a three-dimensional brain blood vessel body data field from CT or MRA equipment; separating the brain blood vessel from background noise through a partitioning algorithm; secondly, calculating the skeleton line of the brain blood vessels, and building a tree-shaped brain blood vessel topological structure as per the skeleton line structure; next, calculating out the radius of the brain blood vessel at each control point through the elastic ball algorithm as per the skeleton line; and finally, three-dimensionally displaying the built brain blood vessels adopting the tree-shaped structure. The construction method provided by the invention accords with information of the space topological structure for brain blood vessels, and has the advantages of high vessel display precision and small result error; and the vessel lesion area can be detected, and the mapping in a multi-scale manner with respect to display windows of different sizes can be realized.

Description

technical field [0001] The invention belongs to the field of medicine, and in particular relates to a method for constructing a three-dimensional blood vessel model based on a tree structure. Background technique [0002] Existing vascular modeling techniques can be roughly divided into two categories: model-free methods and model-based methods. [0003] The most typical and common surface reconstruction method in the free model method is the MC (Marching Cubes) algorithm. This method divides the space into two parts to achieve the purpose of reconstruction by selecting an appropriate threshold and calculating an isosurface by linear interpolation. However, the use of linear interpolation and the thresholding of the space into two parts are too simple, so the reconstruction effect is not ideal. Smoothing is required after reconstruction to remove the aliasing effect of the surface, and simple Laplacian smoothing methods will destroy small branches. Taubin proposed a low-p...

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Problems solved by technology

However, the use of linear interpolation and the thresholding of the space into two parts are too simple, so the reconstruction effect is not ideal

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