Pulmonary nodule three-dimensional segmentation and feature extraction method and system thereof

Abstract

The invention belongs to the application field of computer analysis technology of medical image, and relates to a pulmonary nodule three-dimensional segmentation and feature extraction method and a system thereof based on chest CT. By adopting a level set method based on a three-dimensional space, pulmonary nodule is divided within a three-dimensional interest area, and the feature of the nodule can be extracted by combining the characteristics of a bounding curved surface and the interest area of the pulmonary nodule. The invention comprises a lung area segmentation module, a three-dimensional interest area extracting module, a pulmonary nodule three-dimensional segmentation module, a nodule feature extraction and quantification module and an output module. The invention fully utilizes the three-dimensional space information of HRCT image, thus reducing the interference of normal tissues around the nodule for segmentation and feature extraction, and improving the accuracy of feature extraction.

Description

technical field [0001] The invention belongs to the application field of computer analysis technology of medical images, and in particular relates to a method and system for three-dimensional segmentation and feature extraction of pulmonary nodules based on chest CT. Background technique [0002] With the continuous deterioration of the environment caused by air pollution and the large increase in the smoking population, the incidence and mortality of lung diseases are also increasing year by year. Lung cancer is the number one cause of cancer death in both men and women in most countries around the world. In my country, the number of patients with lung cancer has increased by about 120,000 in the past 5 years; 1 out of every 4 cancer deaths is a lung cancer patient. Since the lung lesions are difficult to be detected in the early stage, by the time clinical symptoms appear and seek medical treatment, most patients have already reached the middle and late stages of the dise...

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Problems solved by technology

For example, the patent document with publication number CN101556650A directly extracts features from the region of interest, such as lobulation sign and cavity sign, without obtaining the boundaries of pulmonary nodules, but the region of interest also contains other normal tissues. These tissue characteristics Feature extraction for regions of interest can be disruptive

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