Interpretation on Breast Cancer Generation in 2D & 3D Images by Skeletonization Algorithm
Madhavi Pingili1, E G Rajan2
1Madhavi Pingili*, Research Scholar, Dept. of Computer Science, MG-NIRSA, Affiliated to University of Mysore, Manasagangotri, Mysore, Karnataka, India.
2Prof. E.G. Rajan, Director, MG-NIRSA, University of Mysore, Mysore, India.
Manuscript received on October 06, 2020. | Revised Manuscript received on October 25, 2020. | Manuscript published on November 30, 2020. | PP: 309-313 | Volume-9 Issue-4, November 2020. | Retrieval Number: 100.1/ijrte.D4995119420 | DOI: 10.35940/ijrte.D4995.119420
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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: The present usage and values obtained clinically on breast cancer expansion and assessment techniques are tragically not upto the mark. In this advanced world, 3D mammography algorithm is not used till now for identifying cancer expansion. A specialized algorithm called skeletonization algorithm is used after identifying the cancer in women’s breast and estimating the direction of spreading cancer and its malignancy. For this 2D and 3D breast images are taken for clinical experiment.
Keywords: Breast Cancer, Lactal Carcinoma, 2D Breast Cancer Spread, 3D Breast Cancer Spread.