Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2014 · 45 citations · 11 references
MedicinePathologyCytopathologyHistologyHistopathologyColor AnalysisColor ImagingHistological StainingMedical Image AnalysisStaining TechniquesClusteringColor Constancy EvaluationColor Distribution AnalysisHistopathological Image AnalysisHistopathology Image AnalysisPathology Image AnalysisStain StandardizationStandardization
This paper presents data on the sources of variation of the widely used hematoxylin and eosin (H&E) histological staining, as well as a new algorithm to reduce these variations in digitally scanned tissue sections. Experimental results demonstrate that staining protocols in different laboratories and staining on different days of the week are the major factors causing color variations in histopathological images. The proposed algorithm for standardizing histology slides is based on an initial clustering of the image into two tissue components having different absorption characteristics for different dyes. The color distribution for each tissue component is standardized by aligning the 2D histogram of color distribution in the hue-saturation-density (HSD) model. Qualitative evaluation of the proposed standardization algorithm shows that color constancy of the standardized images is improved. Quantitative evaluation demonstrates that the algorithm outperforms competing methods. In conclusion, the paper demonstrates that staining variations, which may potentially hamper usefulness of computer assisted analysis of histopathological images, can be reduced considerably by applying the proposed algorithm.
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Pattern Recognition and Machine Learning
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