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Stomach computed tomography (CT) sequence image segmentation method based on interactive region growth

A technology of region growing and sequential images, applied in the field of image processing, can solve problems such as under-segmentation, large changes, noise, etc., and achieve the effect of overcoming under-segmentation and improving speed

Inactive Publication Date: 2012-08-01
XIDIAN UNIV
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Problems solved by technology

However, if the target to be segmented is the lymph node area 5cm around the gastric wall in the CT sequence of the stomach, the segmentation effect is poor.
This is because these target areas are not only irregular in shape, but also vary greatly, and there may be noise, blood vessels and other interference points in the target area, and the existing sequence segmentation methods based on region growth are performed in series, so segmenting such targets Regions are not only slow, but also prone to under-segmentation

Method used

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  • Stomach computed tomography (CT) sequence image segmentation method based on interactive region growth
  • Stomach computed tomography (CT) sequence image segmentation method based on interactive region growth
  • Stomach computed tomography (CT) sequence image segmentation method based on interactive region growth

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Embodiment Construction

[0026] refer to figure 1 , the present invention is based on interactive region growing gastric CT sequence image segmentation method comprises the following steps:

[0027] Step 1: Input gastric CT sequence images, a total of 30 images;

[0028] Step 2: Subtract the adipose tissue area in these 30 images with a given mask image to avoid mis-segmentation, the adipose tissue area such as image 3 As shown, the mask image as Figure 4 shown;

[0029] Step 3: Use interactive region growing to segment the first image I in the 30 images, the first image is as follows Figure 5 Shown:

[0030] refer to figure 2 , the specific implementation of this step is as follows:

[0031] 3a) in Figure 5 Manually select k seed points in the area to be segmented, set a matrix Y that stores the segmentation results with the same size as the image I, and then give a similarity threshold T, where k is an integer greater than 0;

[0032] 3b) Will Figure 5 Each pixel value in the matrix Y...

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Abstract

The invention discloses a stomach computed tomography (CT) sequence image segmentation method based on interactive region growth, which mainly solves the problems that in the prior art, CT sequence segmentation speed is slow, and poor segmentation is easy to occur. The method includes: firstly, a seed point is selected manually in a target area to be segmented in a first image, the interactive region growth is used for performing segmentation, a center of a segmentation result and eight neighborhoods of the center are projected into a next CT image to serve as seed points, the interactive region growth is continuously used for performing segmentation to obtain the target area of the current image, and the segmentation result of the previous image is projected into a next image repeatedly to serve as a seed point to be segmented continuously until segmentation of a whole sequence is completed. Compared with a traditional serial region growth, the stomach CT sequence image segmentation method based on the interactive region growth has the advantages of being rapid in speed, good in effect and the like, can be used for segmenting stomach CT sequence images, and can well segment target areas which may occur in stomach lymph gland in the sequence.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to the processing of medical images, and can be mainly used for the segmentation of gastric CT sequence images. Background technique [0002] With the rapid development of medical imaging technology, a large number of high-resolution images have emerged, such as magnetic resonance imaging MRI, computed tomography CT, magnetoencephalography MEG, three-dimensional ultrasound imaging, solution positron emission tomography PET, single photon emission computed tomography SPECT, diffusion weighted imaging DWI, functional magnetic resonance FMRI, etc., these imaging techniques have their own characteristics, and they can provide people with various anatomical and functional information at different temporal and spatial resolutions. However, relying solely on the information provided by these devices is far from meeting people's requirements, and the image must be further analyzed ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 缑水平王云利周治国刘芳张晓鹏唐磊王之龙马丽敏
Owner XIDIAN UNIV
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