Konstantin Korotkov1, Rafael Garcia. 1. Computer Vision and Robotics Research Group, University of Girona, Campus Montilivi, Edifici P-4, 17071 Girona, Spain. konstantin.korotkov@udg.edu
Abstract
OBJECTIVE: Computerized analysis of pigmented skin lesions (PSLs) is an active area of research that dates back over 25years. One of its main goals is to develop reliable automatic instruments for recognizing skin cancer from images acquired in vivo. This paper presents a review of this research applied to microscopic (dermoscopic) and macroscopic (clinical) images of PSLs. The review aims to: (1) provide an extensive introduction to and clarify ambiguities in the terminology used in the literature and (2) categorize and group together relevant references so as to simplify literature searches on a specific sub-topic. METHODS AND MATERIAL: The existing literature was classified according to the nature of publication (clinical or computer vision articles) and differentiating between individual and multiple PSL image analysis. We also emphasize the importance of the difference in content between dermoscopic and clinical images. RESULTS: Various approaches for implementing PSL computer-aided diagnosis systems and their standard workflow components are reviewed and summary tables provided. An extended categorization of PSL feature descriptors is also proposed, associating them with the specific methods for diagnosing melanoma, separating images of the two modalities and discriminating references according to our classification of the literature. CONCLUSIONS: There is a large discrepancy in the number of articles published on individual and multiple PSL image analysis and a scarcity of reported material on the automation of lesion change detection. At present, computer-aided diagnosis systems based on individual PSL image analysis cannot yet be used to provide the best diagnostic results. Furthermore, the absence of benchmark datasets for standardized algorithm evaluation is a barrier to a more dynamic development of this research area.
OBJECTIVE: Computerized analysis of pigmented skin lesions (PSLs) is an active area of research that dates back over 25years. One of its main goals is to develop reliable automatic instruments for recognizing skin cancer from images acquired in vivo. This paper presents a review of this research applied to microscopic (dermoscopic) and macroscopic (clinical) images of PSLs. The review aims to: (1) provide an extensive introduction to and clarify ambiguities in the terminology used in the literature and (2) categorize and group together relevant references so as to simplify literature searches on a specific sub-topic. METHODS AND MATERIAL: The existing literature was classified according to the nature of publication (clinical or computer vision articles) and differentiating between individual and multiple PSL image analysis. We also emphasize the importance of the difference in content between dermoscopic and clinical images. RESULTS: Various approaches for implementing PSL computer-aided diagnosis systems and their standard workflow components are reviewed and summary tables provided. An extended categorization of PSL feature descriptors is also proposed, associating them with the specific methods for diagnosing melanoma, separating images of the two modalities and discriminating references according to our classification of the literature. CONCLUSIONS: There is a large discrepancy in the number of articles published on individual and multiple PSL image analysis and a scarcity of reported material on the automation of lesion change detection. At present, computer-aided diagnosis systems based on individual PSL image analysis cannot yet be used to provide the best diagnostic results. Furthermore, the absence of benchmark datasets for standardized algorithm evaluation is a barrier to a more dynamic development of this research area.