Decision Support System Analysis for Malignant Melanoma Detection
Naveen Raju D1, Hariharan S2, Ramprasath M3, Manickam M4
1Naveen Raju D, Assistant professor, Department of CSE, Saveetha Engineering college, Chennai, Tamilnadu, India.
2Hariharan S, Professor, Deparment of CSE, Saveetha Engineering college, Chennai, Tamilnadu, India.
3Ramprasath M, Associate Professor, Department of CSE, Madanapalle Institute of Technology Science, Chittoor district of Andhra Pradesh, India.
4Manickam M, Associate Professor, Department of CSE, Saveetha Engineering college, Chennai, Tamilnadu, India.
Manuscript received on November 20, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on 30 November, 2019. | PP: 7365-7369 | Volume-8 Issue-4, November 2019. | Retrieval Number: D5300118419/2019©BEIESP | DOI: 10.35940/ijrte.D5300.118419
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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: One of the most deadly dangerous disease is cancer which is among human beings. Skin cancer is of different types that is found recently among humans. Melanoma is one such type of skin cancer which causes majority of death rate. Biopsy method leads to conventional clinical diagnosis for detection of melanoma. The study in this paper presents different benchmarking techniques for melanoma prediction and evaluation. The main challenge is detection of malignant melanoma, which is found to have asymmetrical, irregular borders, notched edges and colour variations. The various stages of skin cancer prediction were analyzed in this paper. A detailed study on various techniques of medical image processing as applied to melanoma images for past years which need the more attention which is discussed here. The techniques and methods that exit are helpful in each of these process are evaluated and summarized. The paper aims at presenting an analysis on to identify on investigation efforts required to group and classify the sub categories available in the literature and to provide a summary of all the available methods for identification of melanoma cancer.
Keywords: Melonama, ABCD Rule, Cancer Predictio.
Scope of the Article: Software & System Security.