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International audienceMedical image segmentation is the foundation of normal and diseasedtissue 3D visualization, operation simulation and visual operation. Inthis paper, we comprehensively use two values that represent the sameobject (body tissue), to segment by the same algorithm implementation.The original CT images are downloaded from the web source, the dog ribtumor CT scan image by GE medical systems, all the experiment of datasetof 312 thoracic CT scans. The core of the segmentation is k-meansclustering algorithm. The segmentation process consisted of two phases:(1) convert CT value to JPG gray value or not use the original CT valueas the data sets for clustering; (2) segmentation bone tissue using thenew k-means clustering algorithm program which is implemented withMATLAB 2012a programming language and for two-dimensional data matrixdirectly. The experiment produced strikingly different results. Theseresults may be indicating that not only the segmentation algorithmof CT image is important, but also the data for segmentationis important too

Segmentation of Small Animal Computed Tomography Images Using Original CT Values and Converted Grayscale Values