Medical Image Segmentation using CT Scans-A Level Set Approach
Sajith A. G1, Hariharan S2
1Sajith A.G, Department of Electrical & Electronics, Sarabhai Institute of Science and Technology, (Kerala), India.
2Hariharan S, Department of Electrical & Electronics, College of Engineering, (Kerala), India.
Manuscript received on 10 May 2013 | Revised Manuscript received on 18 May 2013 | Manuscript Published on 30 May 2013 | PP: 259-263 | Volume-2 Issue-6, May 2013 | Retrieval Number: F0848052613/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Identification of Liver and liver tumors from CT images is of great interest to physicians and image processing researchers. In this paper a simple and clinically useful system has been developed for segmenting the liver tumor from CT images. Level set methods have been widely used in image processing for segmenting the biomedical images such as liver images. Various methods of segmentation were explored, and a few were chosen for implementation and further development. Liver Images were collected and the region of interest was selected. Segmentation has been performed by using Fuzzy C means algorithm followed by fine delineation using level sets. The method could clearly segment the tumor regions and their boundaries are well defined.
Keywords: FCM, Level Set Method, Liver Tumors.
Scope of the Article: Image Security