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.