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Early stage detection of melanoma (one of the most common cancers today) is of major significance for increasing chances of long term survival of affected patients. Over the last decade there have been developments in skin diagnostics, facilitated by the use of technologies such as Total Body Photography (TBP), which provide a complete record of the skin, and by the development of applications on handheld devices seeking to characterize skin lesions as part of routine self-examination. Unfortunately, these processes are rather inefficient, inaccurate, and not fully automated, missing also critical components such as the automated ability to compare between two TBP image sets in order to locate essential new and altered skin lesions. Despite some progress and because of its many flaws, the common practice today for early detection is skin self-examination. However, it is important to note that skin self-examination is usually underestimated by individuals, resulting in poor prognosis. The main objective of the present paper is to present the conceptual architecture of a platform that can address the need for early and accurate detection of skin lesion through a screening solution that will be easily accessible to the general public with the guidance, supervision and inspection of the primary care physician.

2014 4th international conference on wireless mobile communication and healthcare - transforming healthcare through innovations in mobile and wireless technologies (mobihealth)

MARK1 - A Decision Support System for the Early Detection of Malignant Melanoma