Abstract. When attempting to recover the surface color from an image, modelling the illumination contribution per-pixel is essential. In this work we present a novel approach for illumination compensation using multispectral image data. This is done by means of a low-rank decomposition of representative spectral bands with prior knowledge of the reflectance spectra of the imaged surface. Experimental results on synthetic data, as well as on images of real lesions acquired at the university clinic, show that the proposed method significantly improves the contrast between the lesion and the background.

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Cutaneous T-Cell Lymphoma (CTCL) is a cancer type externally characterized by alterations in the coloring of skin. Optical spectroscopy has been proposed for quantification of minimal changes in skin offering itself as an interesting tool for monitoring of CTCL in real-time. However, in order to be used in a valid way, measurements on the lesions have to be taken at the same position and with the same orientation in each session. Combining hand-held optical spectroscopy devices with tracking and acquiring synchronously spectral information with position and orientation, we introduce a novel computer-assisted scheme for valid spectral quantification of disease progression. We further present an implementation for an augmented reality guidance system that allows to find a point previously analyzed with an accuracy of 0.8[mm] and 5.0[deg] (vs. 1.6[mm] and 6.6[deg] without guidance). The intuitive guidance, as well as the preliminary results shows that the presented approach has great potential towards innovative computer-assistance methods for quantification of disease progression.

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