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http://dx.doi.org/10.9708/jksci.2012.17.3.051

Hepatic Vessel Segmentation using Edge Detection  

Seo, Jeong-Joo (Dept. of Information Communications Engineering, Chungnam National University)
Park, Jong-Won (Dept. of Information Communications Engineering, Chungnam National University)
Publication Information
Journal of the Korea Society of Computer and Information / v.17, no.3, 2012 , pp. 51-57 More about this Journal
Abstract
Hepatic vessel tree is the key structure for hepatic disease diagnosis and liver surgery planning. Especially, it is used to evaluate the donors' and recipients' liver for the LDLT(Living Donors Liver Transplantation) and estimate the volumes of left and right hepatic lobes for securing their life in the LDLT. In this study, we propose a method to apply canny edge detection that is not affected by noise to the liver images for automatic segmentation of hepatic vessels tree in contrast abdominal MDCT image. Using histograms and average pixel values of the various liver CT images, optimized parameters of the Canny algorithm are determined. It is more time-efficient to use the common parameters than to change parameters manually according to CT images. Candidates of hepatic vessels are extracted by threshold filtering around the detected the vessel edge. Finally, using a system which detects the true-negatives and the false-positives in horizontal and vertical direction, the true-negatives are added in candidate of hepatic vessels and the false-positives are removed. As a result of the process, the various hepatic vessel trees of patients are accurately reconstructed in 3D.
Keywords
Automatic segmentation of hepatic vessel; MDCT image processing; Edge detection; error correction on horizontal and vertical direction;
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