Abstract
Skin cancer exists in various forms like Melanoma, Basal and Squamous Cell Carcinoma among which Melanoma is the most hazardous and unpredictable. In this paper, we implement an image processing technique for the early detection of Melanoma Skin Cancer using MATLAB which is easy for use as well as detection of Melanoma skin cancer. There are two stages of detection, the first stage is a simple questionnaire which consists of all the common symptoms faced by melanoma affected person and if the report of the first stage comes out to be positive, the patient can go for the second stage, where the input to the system is the lesion skin image. Further, K-means segmentation is used to segment the images followed by feature extraction. The fetched parameter values are, therefore, used to determine whether the particular patient is suffering from skin cancer or not.
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We certify that no funding has been received for conducting this study and preparation of this manuscript. The database utilized in this study is downloaded from a verified source (Medical News Today) and no patients were involved in this work.
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Pal, S., Monica Subashini, M. (2020). Skin Cancer Detection Using Advanced Imaging Techniques. In: Elçi, A., Sa, P., Modi, C., Olague, G., Sahoo, M., Bakshi, S. (eds) Smart Computing Paradigms: New Progresses and Challenges. Advances in Intelligent Systems and Computing, vol 766. Springer, Singapore. https://doi.org/10.1007/978-981-13-9683-0_25
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DOI: https://doi.org/10.1007/978-981-13-9683-0_25
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