Modeling human-perceived quality for the assessment of digitized histopathology color standardization

Color consistency is still one of the most significant problems in whole-slide imaging since even subtle variations of color appearance in digitized slides might cause image misinterpretation by pathologists or by computer-aided diagnosis systems. These variations are mainly caused by differences in laboratory protocols and imaging devices manufactures. In this paper we propose a model for assessing color standardization algorithms in whole-slide histopathology imaging based on two metrics: (i) the color similarity between a template well-stained image and the resulting color-standardized image, and (ii) the structural distortion caused by the application of a color standardization algorithm. We employed the χ2 histogram distance as color distance measure, and the Universal Quality (Q) index for quantifying structural distortion. The developed model produce an overall quality score (OQS) in the range [0, 10] that correlates well with human-perceived color standardization quality. To the best of our knowledge, this is the first attempt to measure the efficacy of color standardization algorithms in digital pathology.