A semantic object segmentation scheme for X-ray body images

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.