[Image-based computer diagnosis of melanoma]

The use of automated diagnostic systems for the diagnosis of melanomas is becoming increasingly more established. These are based on the following four steps: 1) preprocessing, to ensure that disturbing factors are eliminated, 2) segmentation, the separation of the image and the background, 3) extraction and selection of features that provide the highest measure of accuracy for the diagnosis and 4) classification, in which the lesion is assigned to a diagnostic class. Recently, the computer-assisted diagnosis of melanoma has focused on algorithms based on transfer learning, which can make steps 2 and 3 obsolete and provides better results. In this article we also review smartphone applications in the field of melanoma screening and recognition. These applications should be considered with caution as they are available to lay persons although the diagnostic accuracy of these applications has not usually been tested in clinical trials.