Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifying malignant melanoma. This book summarizes the state of the art of the computerized analysis of dermoscopy images, covering dermoscopy image analysis from preprocessing to classification. The text also explores future directions for this exciting subfield of medical image analysis.

Toward a Robust Analysis of Dermoscopy Images Acquired under Different Conditions. A Bioinspired Color Representation for Dermoscopy Image Analysis. Where's the Lesion? Variability in Human and Automated Segmentation of Dermoscopy Images of Melanocytic Skin Lesions. A State-of-the-Art Survey on Lesion Border Detection in Dermoscopy Images. Comparison of Image Processing Techniques for Reticular Pattern Recognition in Melanoma Detection. Global Pattern Classification in Dermoscopic Images. Streak Detection in Dermoscopic Color Images Using Localized Radial Flux of Principal Intensity Curvature. Dermoscopy Image Assessment Based on Perceptible Color Regions. Improved Skin Lesion Diagnostics for General Practice by Computer-Aided Diagnostics. Accurate and Scalable System for Automatic Detection of Malignant Melanoma. Early Detection of Melanoma in Dermoscopy of Skin Lesion Images by Computer Vision-Based System. From Dermoscopy to Mobile Teledermatology. PH2: A Public Database for the Analysis of Dermoscopic Images.