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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Automatic Liver Segmentation of Contrast Enhanced CT Images Based on Histogram Processing
verfasst von : Kyung-Sik Seo, Hyung-Bum Kim, Taesu Park, Pan-Koo Kim, Jong-An Park
Erschienen in: Advances in Natural Computation
Verlag: Springer Berlin Heidelberg
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Pixel values of contrast enhanced computed tomography (CE-CT) images are randomly changed. Also, the middle liver part has a problem to segregate the liver structure because of similar gray-level values of neighboring organs in the abdomen. In this paper, an automatic liver segmentation method using histogram processing is proposed for overcoming randomness of CE-CT images and removing other abdominal organs. Forty CE-CT slices of ten patients were selected to evaluate the proposed method. As the evaluation measure, the normalized average area and area error rate were used. From the results of experiments, liver segmentation using histogram process has similar performance as the manual method by medical doctor.