Efficient Way to Detect Bone Cancer using Image Segmentation
S. P. Anandaraj1, N. Kirubakaran2, S. Ramesh3, J. Surendiran4
1Dr. S.P. Anandaraj, Professor, Department of Computer Science and Engineering, Mallareddy Engineering College for Women, Hyderabad (Telangana), India.
2Dr. N. Kirubakaran, Professor, Department of Electronics and Computer Science and Engineering, Mallareddy Engineering College for Women, Hyderabad (Telangana), India.
3Dr. S. Ramesh, Professor, Department of Electronics and Computer Science and Engineering, Mallareddy Engineering College for Women, Hyderabad (Telangana), India.
4Dr. J. Surendiran, Professor, Department of Electronics and Communication Engineering, Jaya College of Engineering and Technology, India.
Manuscript received on 30 September 2019 | Revised Manuscript received on 12 November 2019 | Manuscript Published on 22 November 2019 | PP: 1850-1854 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F13530986S319/19©BEIESP | DOI: 10.35940/ijeat.F1353.0986S319
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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: Malignant growth is a wild division of irregular cells, which is spread over the parts of the body. Bone disease is one of the sorts of malignancy. Bone malignancy is a pernicious and threatening illness, caused because of uncontrolled division of cells in the bone. The most compromising and usually happened malignancy is bone disease. Prior the location of bone malignant growth is most testing issue. A definitive objective of this paper is to play out an examination on the bone disease pictures to discover the tumor. In this exploration we are looking at K-implies and fluffy C-Means grouping procedures to recognize the presize accuracy tumor part in the bone. In this exploration at first picture experiences into the division procedure and k-implies and Fuzzy C-Means calculations are connected to distinguish the exact tumor part in the bone. In this exploration is completely utilized MATLAB as a programming instrument for the way toward stacking a picture and to perform picture division. For clear comprehension of this exploration the outline and the outcomes will be shown in the sessions of this paper.
Keywords: Tumor, K-Means Algorithm, Image Segmentation.
Scope of the Article: Signal and Image Processing