Dividing method based on CT image liver tumor focus

Abstract

The invention is applicable to the field of medical image processing, and provides a dividing method based on the CT (Computed Tomography) image liver tumor focus. The method comprises the following steps of preprocessing an initial CT image; completing ROI selection on the suspected focus in an interactive way by aiming at the preprocessed CT image; performing texture description on the ROI based on a CT value, and obtaining probability spectrums of the ROI through weighted computation of texture descriptors; building a big data priori knowledge base, determining a focus region probability spectrum threshold value, and dividing the suspected focus based on the threshold value; and completing the volume statistics and the quantization output on the focus. The method has the advantages that a plurality of texture descriptor probability spectrums are obtained based on stable and comparable CT value calculation; meanwhile, the threshold value of the texture descriptor probability spectrums is obtained through manual division calculation based on the priori knowledge base; and the accuracy and the timeliness of the multi-domain liver tumor focus division in the CT image can be realized.

Description

technical field [0001] The invention belongs to the field of medical image processing, in particular to a method for segmenting liver tumor lesions based on CT images. Background technique [0002] The liver is the largest chemical factory in the human body, undertaking important functions such as digestion, detoxification, and secretion. The burden of disease on the Chinese liver is the heaviest in the world. Primary liver cancer is one of the most common malignant tumors in clinic. At present, the incidence of liver cancer in the world is on the rise. According to the "Global Cancer Report 2014" published by the World Health Organization, China's new cancer cases rank first in the world, and the number of new cases and deaths of liver cancer ranks first in the world. At present, the incidence rate of liver cancer in my country is about 25.7 / 100,000, making it the third most deadly malignant tumor after gastric cancer and lung cancer. Early diagnosis of liver cancer is ...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a method for segmenting liver tumor lesions based on CT images, aiming to solve the problem of inability to accurately and quickly realize the segmentation of multi-focal liver tumors

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