Statistical information-based organ vascular tree automatic extraction method

Abstract

The invention discloses a statistical information-based organ vascular tree automatic extraction method. The method comprises the following steps of S1, performing liver segmentation on an abdominal CT image by applying a level set to obtain image sequences only containing a liver part, and performing denoising processing on image data by using improved three-dimensional median filtering; S2, under multiple continuous thresholds, selecting multiple continuous frames with rich blood vessels to perform morphological processing, and obtaining binary images; and S3, defining target function values according to quantity and size information of connected domains, obtaining a plurality of histograms of the target function values, related to the information of the connected domains, of multiple continuous images under the multiple thresholds, performing fixed-size sliding window scanning, and selecting a weighted average value of a threshold interval with most peak values as a global threshold of regional growth; and S4, under related limitations of the global threshold and a pixel value of a center point, obtaining a vascular tree by using three-dimensional regional growth, and performing repair or later processing on the blood vessels through three-dimensional close 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...

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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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