Abstract
In this chapter, we introduce the basic principles of automated diagnosis of CLSM images of skin lesions. Special attention is given to the machine based description and analysis of the tissues in a way that conforms to the diagnostic guidelines of the derma pathologists. Further, the machine learning algorithm for the automated prediction of the pathology and the generated diagnostic rules are discussed and compared with the diagnostic skills of the derma pathologists. The application and performance of the discussed methods are demonstrated by selected studies.
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Acknowledgment
We wish to thank Ms. G. Searle for the critical reading of the text and all the colleagues who enabled this work.
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Wiltgen, M. (2012). Automated Diagnosis and Reflectance Confocal Microscopy. In: Hofmann-Wellenhof, R., Pellacani, G., Malvehy, J., Soyer, H. (eds) Reflectance Confocal Microscopy for Skin Diseases. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21997-9_36
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DOI: https://doi.org/10.1007/978-3-642-21997-9_36
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