Measles Rash Image Detection Using Deep Convolutional Neural Network

Measles is extremely contagious and is one of the leading causes of vaccine-preventable illness and death in developing countries, claiming more than 100,000 lives each year. Measles was declared eliminated in the US in 2000. As a result, an increasing number of US healthcare professionals and the public have never seen the disease. Unfortunately, the Measles resurged in the US in 2019 with 1,282 confirmed cases. To assist in diagnosing measles, we created a dataset of more than 1300 images of a variety of skin conditions and utilized deep convolutional neural network to distinguish measles rash from other skin conditions. On our curated image dataset, our model reaches a classification accuracy 95.2%, a sensitivity 81.7%, and specificity 97.1%. Our model can potentially be used to facilitate an accurate and early detection of measles to help contain measles outbreaks.