Three-dimensional liver CT (computed tomography) image automatically segmenting method based on hyper voxels and graph cut algorithm
A graph cut algorithm and CT image technology, applied in the field of medical image processing, can solve problems such as inaccurate segmentation results, a large number of manual segmentation standards, and slow segmentation speed
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[0047] The extraction process is described in detail with reference to the drawings and actual examples. The image data used comes from the abdominal enhanced CT scan images in the MICCAI 2007 Workshop database. The average size of each CT image is 512*512*208 pixels, and the average resolution is 0.68*0.68*1.6 mm.
[0048] The flowchart of the liver CT image automatic segmentation method based on the supervoxel and graph cut algorithm of the present invention is as follows figure 1 As shown, including the following steps:
[0049] Step 1. For an inputted abdominal CT image I (such as Figure 4 Shown) perform histogram analysis, adaptively enhance the image contrast, and obtain the contrast-enhanced CT image I'(such as Figure 5 Shown). The specific implementation steps are as follows:
[0050] 1.1. Analyze the number of peaks in the image histogram. If there are 2 more obvious peaks, it is a high-contrast image I high (Such as figure 2 a), if there is only one peak, it is a low...
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