Method for three-dimensionally segmenting insubstantial pulmonary nodule based on fuzzy membership model

A technology of fuzzy membership degree and pulmonary nodules, which is applied in the field of medical image processing, can solve the problems of low segmentation accuracy and achieve the effect of low error volume percentage and high coincidence rate

Inactive Publication Date: 2012-01-18
UNIV OF SHANGHAI FOR SCI & TECH
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Problems solved by technology

[0004] The present invention aims at the problem of low segmentation accuracy of current medical images, and proposes a three-dimensional segmentation algorithm for insubstantial pulmonary nodules based on a fuzzy membership degree model to achieve accurate segmentation of insubstantial pulmonary nodules

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  • Method for three-dimensionally segmenting insubstantial pulmonary nodule based on fuzzy membership model
  • Method for three-dimensionally segmenting insubstantial pulmonary nodule based on fuzzy membership model
  • Method for three-dimensionally segmenting insubstantial pulmonary nodule based on fuzzy membership model

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Embodiment Construction

[0031] Such as figure 1 Shown operating process schematic diagram, the specific implementation steps of the present invention are as follows:

[0032] 1. Input chest CT sequence images in DICOM format containing non-substantial pulmonary nodules;

[0033]2. Obtain the three-dimensional region of interest D1 through manual operation. Since chest CT images contain a large number of pixels in non-nodular areas, in order to reduce image storage space and processing time, only the approximate area containing nodules needs to be intercepted here. The following methods can be used: According to the gold standard provided by radiologists, manually determine The center c of the region of interest and the maximum possible radius r of the nodule, the cube obtained with c as the center point and 2r as the side length is the three-dimensional region of interest D1;

[0034] 3. Perform a threshold operation on D1 to remove the highlighted substantive part to obtain image D2. The voxels ...

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Abstract

The invention relates to a method for three-dimensionally segmenting an insubstantial pulmonary nodule based on a fuzzy membership model. The method comprises the following steps of: manually acquiring a region of interest, which includes the insubstantial pulmonary nodule, and performing subsequent processing in the region of interest; removing substantial parts which have larger gray values and comprise blood vessels, calcified points and the like by using threshold operation; establishing the fuzzy membership model of the insubstantial pulmonary nodule, calculating the membership, of each volume pixel, of the insubstantial pulmonary nodule according to the fuzzy membership model, and classifying the volume pixels based on the calculated membership by using a linear discriminant function; and for the insubstantial pulmonary nodule which is connected with the blood vessels, removing the blood vessels by using a Hessian matrix characteristic value, and thus obtaining a final segmentation result by using a three-dimensional connected region mark. Compared with other domestic and foreign methods for segmenting the insubstantial pulmonary nodule in recent years, the method for three-dimensionally segmenting the insubstantial pulmonary nodule based on the fuzzy membership model has the advantage that: the segmentation accuracy of the insubstantial pulmonary nodule is effectively improved.

Description

technical field [0001] The invention relates to a medical image processing technology, in particular to a three-dimensional segmentation method for insubstantial pulmonary nodules based on a fuzzy membership degree model. Background technique [0002] Accurate segmentation of pulmonary nodules is a key step in computer-aided diagnosis of early lung cancer based on CT images. Whether pulmonary nodules can be accurately segmented from CT images will ultimately affect the performance of computer-aided diagnosis systems. Pulmonary nodules are divided into solid pulmonary nodules and non-solid pulmonary nodules. Solid pulmonary nodules are easy to segment due to their clear boundaries and high density. The density of non-solid pulmonary nodules is ground-glass opacity (GGO), with fuzzy edges and no specific shape. Coupled with the influence of image noise and adhesion to blood vessels, segmentation is extremely difficult. At present, there are only a small amount of literature r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T19/20
Inventor 宋佳聂生东王远军李清梦李新军李翠芳常旖旎高婷
Owner UNIV OF SHANGHAI FOR SCI & TECH
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