AN ANDROID-BASED PATTERN RECOGNITION APPLICATION FOR THE CHARACTERIZATION OF EPIDERMAL MELANOMA

Malignant melanoma is currently one of the leading cancers among white-skinned populations around the world, mainly due to the changes in life styles and the significant increase in ultraviolet radiation. Although the mortality rate due to melanomas was about 70%, forty years ago, nowadays, a survival rate of 70% is claimed, which is attributed to early diagnosis. Hence, early stage detection of melanoma is of major significance for increasing chances of long term survival of affected patients. The most effective method for early detection is skin self-examination, a procedure often underestimated by individuals, resulting in poor prognosis. Therefore, the aim of the present study is to address the need for early and accurate characterization of skin lesions through the design and implementation of an Android application that enables users identify areas on their skin that may need attention from an expert physician. The proposed application uses the phone’s camera feature to take a picture of a skin lesion/mole, communicates with a remote specialized pattern recognition system, via a set of XML Web Services, and within seconds receives a risk analysis of their uploaded image being a melanoma. The proposed system was trained using an image database from New Zealand Dermatological Society, and was reviewed by an expert dermatologist. INTRODUCTION Malignant melanoma is nowadays one of the leading cancers among many white-skinned populations around the world, and it has recently dramatically increased mainly due to the changes in life styles and the significant increase in ultraviolet radiation [15] . While the mortality rate due to melanomas was about 70%, forty years ago, nowadays, a survival rate of 70% is claimed, which is attributed to early diagnosis. Therefore, early stage detection of melanoma is of major significance for increasing chances of long term survival of affected patients. The most effective method for early detection is skin self-examination. The individual investigates skin changes, especially in moles (existing or new) and reports to the doctor when suspicious regions require consultation from the medical experts. During the first stages of the disease, complete treatment is most probable for most patients, with at least 5 year survival rates for the 95% of cases. However, it has been shown that skin self-examination is usually underestimated by individuals, resulting in poor prognosis. Melanoma detected in later stages, is extremely aggressive and deadly, resulting in patient suffering and increase mortality/morbidity. This has driven researchers to seek solutions in automated, early diagnosis of skin lesions [1-15] and to render such procedures accessible to the general public. Automated image analysis systems for the characterization of epidermic melanoma, based on recent technology, can be deployed as an excellent useful tool for prescreening of suspicious regions on human skin. The first studies for automated classification of pigmented skin lesion images are referred in literature from 1987 [16] . Although, those systems cannot provide a definite diagnosis, they can help physicians to focus on certain, suspicious cases, for malignant melanoma. Recently, with the rapid development of handheld devices, such as smartphones and tablets, this need was addressed by applications that reclaim all the recent technology applied, such as the embedded camera and the fast processors [5-8] . The Cronian Labs Corporation has already suggested the “Skin Scan” application for Apple iOS operating system using pattern recognition algorithms and e-Περιοδικό Επιστήμης & Τεχνολογίας e-Journal of Science & Technology (e-JST)