Real-Time Mobile-Phone-Aided Melanoma Skin Lesion Detection Using Triangulation Technique

Abstract

Melanoma is a harmful disease among all types of skin cancer. Genetic factors and the exposure of UV rays causes melanoma skin lesions. Early diagnosis is important to identify malignant melanomas to improve the patient prognosis. A biopsy is a traditional method which is painful and invasive when used for skin cancer detection. This method requires laboratory testing which is not very efficient and time-consuming to detect skin lesions. To solve the above issue, a computer aided diagnosis (CAD) for skin lesion detection is needed. In this article, we have developed a mobile application with the capabilities to segment skin lesions in dermoscopy images using a triangulation method and categorize them into malignant or bengin lesions through a supervised method which is convolution neural network (CNN). This mobile application will make the skin cancer detection non-invasive which does not require any laboratory testing, making the detection less time consuming and inexpensive with a detection accuracy of 81%.

Disruptive Technology Enabled Healthcare 4.0 Model for Lesion Identification with Reduced Latency

“…Any anomaly on the skin or in medical terms, a superficial growth or spot on the skin which cannot resemble the area around it, is termed as skin lesion [31]. Skin lesion is caused due to various bacteria, viruses, parasites or fungi and warts, moles, actinic keratosis and chickenpox are best examples of skin infections and may lead to skin cancer.…”