An Automatic Extraction Method of Organ Vascular Tree Based on Statistical Information

Abstract

The invention discloses a method for automatically extracting organ vascular trees based on statistical information, which includes the following steps: S1: Segment the liver on abdominal CT images using level sets to obtain an image sequence containing only liver parts, and use an improved method for image data Three-dimensional median filtering for denoising processing; S2: under continuous multiple thresholds, select continuous multi-frames rich in blood vessels for morphological processing and obtain binary images; S3: define the objective function value by the number and size information of connected domains, Obtain multiple histograms of objective function values ​​related to connected domain information under multiple thresholds in consecutive images, perform a fixed-size sliding window scan, and select the weighted average value of the threshold interval with the most peaks as a global threshold S4 for region growth : Under the relevant constraints of the global threshold and the pixel value of the center point, a vascular tree is obtained by using 3D region growth, and the vascular tree is repaired or post-processed through the 3D closing operation.

Description

technical field [0001] The invention relates to the field of computer image processing, in particular to an automatic extraction method of an organ vascular tree based on statistical information. Background technique [0002] Liver resection is an important method in the treatment of liver cancer and liver tumors. Local resection centered on liver tumors is an important surgical method of liver resection, but it is easy to cut off important blood vessels during the operation, resulting in extensive liver tissue ischemia, congestion and even necrosis. Using computer technology to extract the three-dimensional vascular tree, three-dimensionally display the real spatial relationship between the tumor and the surrounding blood vessels, so that doctors can formulate a more detailed and reasonable liver resection plan, so it has important clinical value. After years of development, research experts have proposed many extraction methods of intrahepatic vascular trees, the main met...

AI Technical Summary

Problems solved by technology

[0003] Due to various unfavorable factors such as the tail shadow left by the previous phase of data, image noise, large number of intrahepatic blood vessels, complex blood vessel shape, and the presence of tumors in the collected CT image data, it is difficult to extract blood vessels.

An effective means of intrahepatic blood vessel extraction is through regional growth, but the relevant preprocessing and threshold selection is a difficult problem. Based on the local threshold and growth criteria, it is easy to cause the grown blood vessels to become flakes or too few. There is an urgent need for those skilled in the art to solve the corresponding technical problems

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