title: New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.
abstract: BACKGROUND
  Accurate evaluation of immunostained histological images is required for reproducible research in many different areas and forms the basis of many clinical decisions. The quality and efficiency of histopathological evaluation is limited by the information content of a histological image, which is primarily encoded as perceivable contrast differences between objects in the image. However, the colors of chromogen and counterstain used for histological samples are not always optimally distinguishable, even under optimal conditions.
  
  
  RESULTS
  In this study, we present a method to extract the bivariate color map inherent in a given histological image and to retrospectively optimize this color map. We use a novel, unsupervised approach based on color deconvolution and principal component analysis to show that the commonly used blue and brown color hues in Hematoxylin-3,3'-Diaminobenzidine (DAB) images are poorly suited for human observers. We then demonstrate that it is possible to construct improved color maps according to objective criteria and that these color maps can be used to digitally re-stain histological images.
  
  
  RESULTS
  To validate whether this procedure improves distinguishability of objects and background in histological images, we re-stain phantom images and N = 596 large histological images of immunostained samples of human solid tumors. We show that perceptual contrast is improved by a factor of 2.56 in phantom images and up to a factor of 2.17 in sets of histological tumor images.
  
  
  BACKGROUND
  Thus, we provide an objective and reliable approach to measure object distinguishability in a given histological image and to maximize visual information available to a human observer. This method could easily be incorporated in digital pathology image viewing systems to improve accuracy and efficiency in research and diagnostics.
authors.affiliation: Institute of Pathology, University Medical Center Mannheim, University of Heidelberg, Mannheim, Germany.|Computer Assisted Clinical Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
authors.forename: Jakob Nikolas
authors.initials: JN
authors.lastname: Kather
authors.affiliation: Institute of Pathology, University Medical Center Mannheim, University of Heidelberg, Mannheim, Germany.
authors.forename: Cleo-Aron
authors.initials: CA
authors.lastname: Weis
authors.affiliation: Institute of Pathology, University Medical Center Mannheim, University of Heidelberg, Mannheim, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Marx
authors.affiliation: Department of Ophthalmology, Mainz University Medical Center, Mainz, Germany.
authors.forename: Alexander K
authors.initials: AK
authors.lastname: Schuster
authors.affiliation: Computer Assisted Clinical Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
authors.forename: Lothar R
authors.initials: LR
authors.lastname: Schad
authors.affiliation: Computer Assisted Clinical Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
authors.forename: Frank Gerrit
authors.initials: FG
authors.lastname: Zöllner
mesh_terms: D015100:3,3'-Diaminobenzidine / Q000378:metabolism; D003116:Color; D004396:Coloring Agents / Q000378:metabolism*; D006416:Hematoxylin / Q000378:metabolism; D006652:Histological Techniques / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D009369:Neoplasms / Q000175:diagnosis* / Q000378:metabolism; D013194:Staining and Labeling / Q000379:methods*
chemical_list: D004396:Coloring Agents; D015100:3,3'-Diaminobenzidine; D006416:Hematoxylin