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New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

Kather JN, Weis CA, Marx A, Schuster AK, Schad LR, Zöllner FG - PLoS ONE (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Institute of Pathology, University Medical Center Mannheim, University of Heidelberg, Mannheim, Germany.

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.

Methods and 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.

Validation: 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.

Context: 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.

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Related in: MedlinePlus

New color maps offer higher perceptual contrast than original color map in all relevant color map regions.A) Original image. B) Image re-stained with the optimized red (#FF0000)—blue (#0093FF) color map. C) Image re-stained with the optimized blue (#006EFF)—orange (#FFAD00) color map. A.1, B.1, C.1) Corresponding bivariate color maps. A.2, B.2, C.2) Intensity represents perceptual contrast (CIELAB distance) of A.1, B.2, C.1 relative to the center point. It can be seen that perceptual contrast of the original color map is low in almost all regions while the perceptual contrast of the new color maps is much higher.
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pone.0145572.g005: New color maps offer higher perceptual contrast than original color map in all relevant color map regions.A) Original image. B) Image re-stained with the optimized red (#FF0000)—blue (#0093FF) color map. C) Image re-stained with the optimized blue (#006EFF)—orange (#FFAD00) color map. A.1, B.1, C.1) Corresponding bivariate color maps. A.2, B.2, C.2) Intensity represents perceptual contrast (CIELAB distance) of A.1, B.2, C.1 relative to the center point. It can be seen that perceptual contrast of the original color map is low in almost all regions while the perceptual contrast of the new color maps is much higher.

Mentions: After determining the optimal combination of colors for bivariate color maps, we applied these color maps to a sample image of a blood vessel in human colorectal cancer (Fig 5). In Fig 5A, we show a sample histological image which is re-stained in 5B and 5C. The corresponding color maps are shown in Fig 5A.1–C.1.


New Colors for Histology: Optimized Bivariate Color Maps Increase Perceptual Contrast in Histological Images.

Kather JN, Weis CA, Marx A, Schuster AK, Schad LR, Zöllner FG - PLoS ONE (2015)

New color maps offer higher perceptual contrast than original color map in all relevant color map regions.A) Original image. B) Image re-stained with the optimized red (#FF0000)—blue (#0093FF) color map. C) Image re-stained with the optimized blue (#006EFF)—orange (#FFAD00) color map. A.1, B.1, C.1) Corresponding bivariate color maps. A.2, B.2, C.2) Intensity represents perceptual contrast (CIELAB distance) of A.1, B.2, C.1 relative to the center point. It can be seen that perceptual contrast of the original color map is low in almost all regions while the perceptual contrast of the new color maps is much higher.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4696851&req=5

pone.0145572.g005: New color maps offer higher perceptual contrast than original color map in all relevant color map regions.A) Original image. B) Image re-stained with the optimized red (#FF0000)—blue (#0093FF) color map. C) Image re-stained with the optimized blue (#006EFF)—orange (#FFAD00) color map. A.1, B.1, C.1) Corresponding bivariate color maps. A.2, B.2, C.2) Intensity represents perceptual contrast (CIELAB distance) of A.1, B.2, C.1 relative to the center point. It can be seen that perceptual contrast of the original color map is low in almost all regions while the perceptual contrast of the new color maps is much higher.
Mentions: After determining the optimal combination of colors for bivariate color maps, we applied these color maps to a sample image of a blood vessel in human colorectal cancer (Fig 5). In Fig 5A, we show a sample histological image which is re-stained in 5B and 5C. The corresponding color maps are shown in Fig 5A.1–C.1.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Institute of Pathology, University Medical Center Mannheim, University of Heidelberg, Mannheim, Germany.

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.

Methods and 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.

Validation: 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.

Context: 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.

Show MeSH
Related in: MedlinePlus