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21 May 1999 Semantic object segmentation scheme for x-ray body images
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In the segmentation process based on a watershed algorithm, a proper seed extraction is very important for segmentation quality because improper seeds can produce undesirable results such as over-segmentation or under-segmentation. Especially, an appropriate seed-extraction algorithm is indispensable in segmenting XCT body images where many organs, except lungs and bones, are in very narrow gray-level ranges with very low contrasts. In the proposed scheme, we divide an image into 4 sub-images by windowing its gray-level histogram, and extract proper seeds from each sub-image by different method according to its characteristic. Then, by using all the seeds obtained from the four separated sub-images, we perform the watershed algorithm to complete the image segmentation. The proposed segmentation method has been successfully applied to X-ray CT body images.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jaeyoun Yi, Hyun Sang Park, and Jong Beom Ra "Semantic object segmentation scheme for x-ray body images", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999);

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