Feature-preserving artifact removal from dermoscopy images

Dermoscopy, also called surface microscopy, is a non-invasive imaging procedure developed for early screening of skin cancer. With recent advance in skin imaging technologies and image processing techniques, there has been increasing interest in computer-aided diagnosis of skin cancer from dermoscopy images. Such diagnosis requires the identification of over one hundred cutaneous morphological features. However, computer procedures designed for extracting and classifying these intricate features can be distracted by the presence of artifacts like hair, ruler markings, and air bubbles. Therefore, reliable artifact removal is an important pre-processing step for improving the performance of computer-aided diagnosis of skin cancer. In this paper, we present a new scheme that automatically detects and removes hairs and ruler markings from dermoscopy images. Moreover, our method also addresses the issue of preserving morphological features during artifact removal. The key components of this method include explicit curvilinear structure detection and modeling, as well as feature guided exemplar-based inpainting. We experiment on a number of dermoscopy images and demonstrate that our method produces superior results compared to existing techniques.