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. With video-assisted surgery devices becoming more common in all fields of diagnostics and therapy, the question of how well such systems are able to reproduce surface colors of organic tissue arises, especially in cases where a proper distinction of different kinds of tissue—not only through their texture but also through their color—might be crucial for the success of a surgery. Since modern devices are usually made of a highly efficient, multispectral LED light source in combination with some light-guiding structures and a digital camera system, an approach of optimizing these systems’ color reproduction properties based on the estimation of in-situ spectral reflectances is proposed. Following the International Organization for Standardization (ISO) standard procedure of colorimetric characterization, an initial color correction matrix was determined first by solving a linear least-mean-squares optimization problem for a small set of artificial color samples mapping the corresponding camera responses onto the samples’ tristimulus values. This initial matrix was then used as a starting point for a second, nonlinear optimization, which makes use of the estimated reflectance spectra in order to minimize the average squared color difference between the color corrected and the actually perceived tristimulus values of the individual organic tissue samples. Compared to the ISO standard, which only knows simple color patches to be used for the nonlinear optimization, a significant enhancement in the color reproduction of organic tissue could be confirmed with the newly proposed method being applied instead.

Spectral reflectance estimation of organic tissue for improved color correction of video-assisted surgery