Abstract
This paper proposes a content-based image retrieval system for skin lesion images as a diagnostic aid. The aim is to support decision making by retrieving and displaying relevant past cases visually similar to the one under examination. Skin lesions of five common classes, including two non-melanoma cancer types are used. Colour and texture features are extracted from lesions. Feature selection is achieved by optimising a similarity matching function. Experiments on our database of 208 images are performed and results evaluated.
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Ballerini, L., Li, X., Fisher, R.B., Rees, J. (2010). A Query-by-Example Content-Based Image Retrieval System of Non-melanoma Skin Lesions. In: Caputo, B., Müller, H., Syeda-Mahmood, T., Duncan, J.S., Wang, F., Kalpathy-Cramer, J. (eds) Medical Content-Based Retrieval for Clinical Decision Support. MCBR-CDS 2009. Lecture Notes in Computer Science, vol 5853. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11769-5_3
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DOI: https://doi.org/10.1007/978-3-642-11769-5_3
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