An Automatic Segmentation of Kidney in Serial Abdominal CT Scans Using Region Growing Approach |
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Authors: | GAO Yan WANG Bo-liang |
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Institution: | Department of Cognitive Science, Fujian Key Laboratory of the Brain-like Intelligent Systems, Xiamen University, Xiamen 361005, China |
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Abstract: | Automatic kidney segmentation from abdominal CT images is a key step in computer-aided diagnosis for kidney CT as well as computer-aided surgery. However, kidney segmentation from CT images is generally performed manually or semi-automatically because of gray levels similarities of adjacent organs/tissues in abdominal CT images. This paper presents an efficient algorithm for segmenting kidney from serials of abdominal CT images. First, we extracted estimated kidney position (EKP) according to the statistical geometric location of kidney within the abdomen. Second, we analyzed the intensity distribution of EKP for several abdominal CT images and exploit an adaptive threshold searching algorithm to eliminate many other organs/tissues in the EKP. Finally, a novel region growing approach based on labeling is used to obtain the free kidney regions. Experimental results are comparable to those of manual tracing radiologist and shown to be efficient. |
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Keywords: | abdominal CT images kidney segmentation estimated kidney position (EKP) adaptive region growing |
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