EARLY DIAGNOSIS OF SKIN CANCER USING ARTIFICIAL NEURAL NETWORKS

Birajdar Yogesh; Rengaprabhu P

doi:10.29121/granthaalayah.v5.i4RACSIT.2017.3341

Authors

Birajdar Yogesh Department of electronics and communication, Don Bosco Institute Of Technology, Bangalore, India
RengaprabhuP Department of electronics and communication, Don Bosco Institute Of Technology, Bangalore, India

DOI:

https://doi.org/10.29121/granthaalayah.v5.i4RACSIT.2017.3341

Keywords:

Classification, Feature Selection, Image Processing, Snake Segmentation, Support Vector Machine

Abstract [English]

The proposed work is to present an approach to easily detect the skin cancer and classify into benign and malignant classes differentiating with the wounds. The skin cancer occurs for many people in some regions of the countries like Australia & New Zealand where the sunlight is difficult to reach during winters. Thus the deficiency of Vitamin D causes skin cancer for the people dwelling in such regions. Self-assessment is being encouraged in such cities to detect the skin cancers in early stages. It is very much essential to diagnose the skin cancer in the early stages and help the patients to get the treatment effectively. The proposed system is supposed to match the self-assessment need for the people to take care of themselves in very less time and regular basis.

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