Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily 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.
Dermoscopy Image Analysis summarizes the state of the art of the computerized analysis of dermoscopy images. The book begins by discussing the influence of color normalization on classification accuracy and then:
Dermoscopy Image Analysis not only showcases recent advances but also explores future directions for this exciting subfield of medical image analysis, covering dermoscopy image analysis from preprocessing to classification.
"… demonstrates the significant advancements in dermoscopy image analysis techniques, involving image-preprocessing, lesion segmentation (or border detection), feature extraction, pattern analysis, lesion classification, and database construction. The approaches described are state of the art and the details are sine qua non. … a good addition on the dermatologist and researcher’s bookshelf, and pilots further research in this field."
—Fengying Xie, Image Processing Center, Beihang University, Beijing, China
"… a comprehensive description of computerized image analysis that is definitely useful for researchers in this field as a starting point for future developments."
—Giuseppe Argenziano, Dermatology Unit, Second University of Naples, Italy
"… collect[s] high-quality research articles on dermoscopy image analysis. … presents the latest state-of-the-art techniques for classifying benign and malignant skin lesions. A very interesting point that emerged from the literature review, as one author points out, is that all these computer-aided diagnosis (CAD) systems offer invaluable help to the general practitioner (GP) in an initial diagnosis of the lesions. The high level of performance of these systems can thus provide an accurate evaluation of skin lesions without having to refer to a dermatologist at this initial stage."
—Lucia Ballerini, University of Edinburgh, Scotland
"… deals with a very important and hot topic that attracts the interest of many researchers and doctors in the scientific community nowadays. … well written and clear. It provides a good overview of the dermoscopy image analysis field, and it is useful for engineers and computer scientists interested in developing similar applications, since it includes in-depth technical descriptions."
—Ilias Maglogiannis, University of Piraeus, Greece
"… I definitely would like to have this book [on] my shelf. … a valuable resource for researchers and graduate students of computer vision and medical image analysis interested in skin cancer detection methods for dermoscopic images. It covers fundamentals of the area by providing thorough treatments of the theory and the concepts while making the material accessible to the reader with examples that nicely illustrate the concepts."
—Jacob Scharcanski, Universidade Federal do Rio Grande do Sul, Brazil
"… provides a comprehensive, well-rounded coverage on the factors, challenges, and state-of-the-art solutions to the very difficult problem of dermascopy image analysis. … a good reference to have in the libraries of researchers in this field."
—Alexander Wong, University of Waterloo, Ontario, Canada
Toward a Robust Analysis of Dermoscopy Images Acquired under Different Conditions
Catarina Barata, M. Emre Celebi, and Jorge S. Marques
A Bioinspired Color Representation for Dermoscopy Image Analysis
Ali Madooei and Mark S. Drew
Where’s the Lesion? Variability in Human and Automated Segmentation of Dermoscopy Images of Melanocytic Skin Lesions
Federica Bogo, Francesco Peruch, Anna Belloni Fortina, and Enoch Peserico
A State-of-the-Art Survey on Lesion Border Detection in Dermoscopy Images
M. Emre Celebi, Quan Wen, Hitoshi Iyatomi, Kouhei Shimizu, Huiyu Zhou, and Gerald Schaefer
Comparison of Image Processing Techniques for Reticular Pattern Recognition in Melanoma Detection
Jose Luis García Arroyo and Begoña García Zapirain
Global Pattern Classification in Dermoscopic Images
Aurora Sáez, Carmen Serrano, and Begoña Acha
Streak Detection in Dermoscopic Color Images Using Localized Radial Flux of Principal Intensity Curvature
Hengameh Mirzaalian, Tim K. Lee, and Ghassan Hamarneh
Dermoscopy Image Assessment Based on Perceptible Color Regions
Gunwoo Lee, Onseok Lee, Jaeyoung Kim, Jongsub Moon, and Chilhwan Oh
Improved Skin Lesion Diagnostics for General Practice by Computer-Aided Diagnostics
Kajsa Møllersen, Maciel Zortea, Kristian Hindberg, Thomas R. Schopf, Stein Olav Skrøvseth, and Fred Godtliebsen
Accurate and Scalable System for Automatic Detection of Malignant Melanoma
Mani Abedini, Qiang Chen, Noel C. F. Codella, Rahil Garnavi, and Xingzhi Sun
Early Detection of Melanoma in Dermoscopy of Skin Lesion Images by Computer Vision-Based System
Hoda Zare and Mohammad Taghi Bahreyni Toossi
From Dermoscopy to Mobile Teledermatology
Luís Rosado, Maria João M. Vasconcelos, Rui Castro, and João Manuel R. S. Tavares
PH2: A Public Database for the Analysis of Dermoscopic Images
Teresa F. Mendonça, Pedro M. Ferreira, André R. S. Marçal, Catarina Barata, Jorge S. Marques, Joana Rocha, and Jorge Rozeira