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Dr. Assoc. Prof. Ahmad Taher Azar :: Publications:

Title:
Automatic computer aided segmentation for liver and hepatic lesions using hybrid segmentations techniques. International Workshop on Artificial Intelligence in Medical Applications (AIMA'13) Kraków, Poland, September 8-11, 2013
Authors: Ahmed M. Anter, Ahmad Taher Azar, Nashwa El-Bendary, Abul Ella Hassenian, Mohamed Abu ElSoud
Year: 2013
Keywords: Not Available
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: International
Paper Link: Not Available
Full paper Ahmad Taher Azar_143.pdf
Supplementary materials Not Available
Abstract:

Liver cancer is one of the major death factors in the world. Transplantation and tumor resection are two main therapies in common clinical practice. Both tasks need image assisted planning and quantitative evaluations. An efficient and effective automatic liver segmentation is required for corresponding quantitative evaluations. Computed Tomography (CT) is highly accurate for liver cancer diagnosis. Manual identification of hepatic lesions done by trained physicians is a time-consuming task and can be subjective depending on the skill, expertise and experience of the physician. Computer aided segmentation of CT images would thus be a great step forward to scienti?c advancement for medical purposes. The sophisticated hybrid system was proposed in this paper which is capable to segment liver from abdominal CT and detect hepatic lesions automatically. The proposed system based on two different datasets and experimental results show that the proposed system robust, fastest and effectively detect the presence of lesions in the liver, count the distinctly identifiable lesions and compute the area of liver affected as tumors lesion, and provided good quality results, which could segment liver and extract lesions from abdominal CT in less than 0.15 s/slice.

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