Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, preprocessing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique's performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided.
In the review REF the state of the art of melanoma CAD was examined: in-vivo imaging techniques, image acquisition, pre-processing, segmentation methods, feature extraction and selection, and classification of dermoscopic images.
Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms
International Journal of Biomedical Imaging
International Journal of Biomedical Imaging
Computer Science Medicine