Smartphone App for Skin Cancer Mole Detection
Melanoma is a particularly dangerous type of skin cancer and is hard to treat in its later stages. Therefore, early detection is key in reducing mortality rates. In order to assist dermatologists in doing this, computer-aided systems have been designed for desktop computers. However, there is a desire for the development of mobile, at-home diagnostics for melanoma risk assessment. Here, we introduce a smartphone application that captures images and extracts ABCD features to classify skin lesions as either malignant or benign. The algorithms used are adaptive to make the process light and user-friendly, as well as reliable in diagnosis. Images can be taken with the phone's camera or imported from public datasets. The entire process of taking the image, performing preprocessing, segmentation and classification is completed on an Android smartphone in a short time. Our application is evaluated on a dataset of 200 images, and achieved either comparable or better performance metrics than other methods. Additionally, it is easy-to-download and easy-to-navigate for the user, which is important for the widespread use of such diagnostics.
Kalwa, U.; Legner, C.; Kong, T.; Pandey, S. Skin Cancer Diagnostics with an All-Inclusive Smartphone Application. Symmetry 2019, 11, 790. https://doi.org/10.3390/sym11060790
