Segmentation method of viscera and internal blood vessels thereof in surgical planning system

Abstract

The invention relates to a segmentation method of medical images, and specifically relates to a segmentation method of viscera and internal blood vessels thereof in a surgical planning system. The method designs a segmentation method of images of liver parenchyma, portal veins and hepatic veins based on minimal supervised classification of the three-dimensional CT images of the viscera and internal tubular tissues thereof. The method applies methods of statistics and spatial information, introduces high credible points, and obtains segmentation results based on arrival time of fast march of grey level. The method assumes that spatially adjacent points belong to a same organ, and performs segmentation calculation on the images by using a classification algorithm based on the above assumption, wherein the segmentation calculation comprises the steps of: acquiring estimated values of parameters of a Gaussian mixture distribution model; selecting the high credible points; and calculating the mean value of the grey level of the images and calculating the arrival time by using a fast marching algorithm to obtain arrival time images of three tissue classifications. According to the invention, good robustness and good anti-noise interference capability are obtained, accumulated errors are eliminated effectively, classification accuracy is improved, and great application value in clinical treatment is achieved.

Description

technical field [0001] The segmentation method of viscera and its internal blood vessels in the surgical planning system of the present invention relates to a medical image segmentation method, which is used in the surgical planning system, especially to segment the liver parenchyma, hepatic portal vein and hepatic A vein belongs to the technical field of medical image processing. Background technique [0002] The important work of computer-aided liver surgery planning is to accurately segment the tree structure of liver parenchyma, hepatic portal vein and hepatic vein from original medical images, and make the extracted results as close as possible to the real anatomical structure. In the segmentation problem of the hepatic portal vein and hepatic vein, because the spatial structure and distribution of the hepatic portal vein and hepatic vein vary greatly among different individuals, the gray distribution of the hepatic portal vein and hepatic vein is close to the liver par...

AI Technical Summary

Problems solved by technology

[0008] The emergence of semi-supervised algorithms is mainly based on the following considerations: In most cases, in order to achieve better results for fully supervised classification algorithms, a large amount of labeled data is required, but it is very difficult or very difficult to obtain a large enough labeled data. Time-consuming, and relatively easy to obtain a small amount of labeled data

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