Automatic Liver Parenchyma Segmentation from Abdominal CT Images

Ahmed M. Anter, M. A. Elsoud, and A. E. Hassanien, "Automatic Liver Parenchyma Segmentation from Abdominal CT Images", The 9th IEEE International Computer Engineering Conference (ICENCO 2013) pp. 32 – 36, Cairo, EGYPT -, December 29-30, , 2013.

Date Presented:

December 29-30,

Related External Link

This article introduces hybrid automatic liver Parenchyma segmentation approach from abdominal CTimages. The proposed approach consist of four main phases. Firstly, preprocessing phase which converts CT image into binary image using adaptive threshold method that examine the intensity values of the local neighborhood of each pixel. Then, the second phase is to apply multi-scale morphological operators to filter tissues nearby liver and to preserve the liver structure and remove the fragments of other organs. The third phase is a post-processing that uses connected component labeling algorithm (CCL) to remove small objects and false positive regions. The algorithm is tested using two different datasets and the experimental results obtained, show that the proposed approach are promising which could segment liver from abdominal CT in less than 0.6 s/slice and the overall accuracy obtained by the proposed approach is 93%.