Introduction to signal processing
Introduction to signal processing
Computer Vision
Digital Image Processing
Random Processes: Filtering, Estimation, and Detection
Random Processes: Filtering, Estimation, and Detection
Automatic segmentation of liver region based on extracted blood vessels
Systems and Computers in Japan
Efficient liver segmentation based on the spine
ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
Automatic Segmentation of Single and Multiple Neoplastic Hepatic Lesions in CT Images
IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
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This paper proposes automatic boundary tumor segmentation for the computer aided liver diagnosis system. As pre-processing, the liver structure is first segmented using histogram transformation, multi-modal threshold, C-class maximum a posteriori decision, and binary morphological filtering. After binary transformation of the liver structure, the image based bounding box is created and convex deficiencies are segmented. Large convex deficiencies are selected by pixel area estimation and selected deficiencies are transformed to gray-level deficiencies. The boundary tumor is selected by estimating the variance of deficiencies. In order to test the proposed algorithm, 225 slices from nine patients were selected. Experimental results show that the proposed algorithm is very useful for diagnosis of the abnormal liver with the boundary tumor.