- 1 - Accepted to be published by Medical Image Analysis Journal From colour to tissue histology: Physics based interpretation of images of pigmented skin lesions Ela Claridge 1 , Symon Cotton 2 , Per Hall 3 , Marc Moncrieff 4 1 School of Computer Science, The University of Birmingham, Birmingham B15 2TT, U.K. 2 Astron Clinica, The Mount, Toft, Cambridge CB3 7RL, U.K. 3 Department of Plastic Surgery, Addenbrooke’s Hospital, Cambridge CB2 2QQ, U.K. 4 Mersey Deanery, Hamilton House, 24 Pall Mall, Liverpool L3, U.K. Abstract Through an understanding of the image formation process, diagnostically important facts about the internal structure and composition of pigmented skin lesions can be derived from their colour images. A physics-based model of tissue colouration provides a cross-reference between image colours and the underlying histological parameters. It is constructed by computing the spectral composition of light remitted from the skin given parameters specifying its structure and optical properties. The model is representative of all the normal human skin colours, irrespective of racial origin, age or gender. Abnormal skin colours do not conform to this model and thus can be detected. Once the model is constructed, for each pixel in a colour image its histological parameters are computed from the model. Represented as images, these “parametric maps” show the concentration of dermal and epidermal melanin, blood and collagen thickness across the imaged skin as well as locations where abnormal colouration exists. In a clinical study the parametric maps were used by a clinician to detect the presence of malignant melanoma in a set of 348 pigmented lesions imaged using a commercial device, the SIAscope. Logistic regression identified the presence of melanin in the dermis, the abnormal distribution of blood within the lesion and the lesion size as the most diagnostically informative features. Classification based on these features showed 80.1% sensitivity and 82.7% specificity in melanoma detection. Keywords Colour analysis, image analysis, physics-based modelling, pigmented skin lesions, melanoma