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Color quantification for evaluation of stained tissues
Author(s) -
Wang Defeng,
Shi Lin,
Wang YiXiang J.,
Man Gene ChiWai,
Heng Pheng Ann,
Griffith James F.,
Ahuja Anil T.
Publication year - 2011
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.21037
Subject(s) - color space , artificial intelligence , computer science , computer vision , color difference , grading (engineering) , prussian blue , pattern recognition (psychology) , biology , image (mathematics) , chemistry , ecology , enhanced data rates for gsm evolution , electrode , electrochemistry
The objective evaluation of the color and shade in stained images remains unsolved and is frequently and extensively encountered in biomedical studies. Most of the evaluations on the color and shade in the stained images are currently performed by subjective grading, which is prone to be affected by inter‐reader variation. This paper introduces a novel approach to automatically quantify the color and shade in the stained histological image based on its similarity map in the CIELAB color space with respect to a user specified reference color. The proposed algorithm was applied on three datasets, i.e., a phantom image, the Prussian blue staining of human osteosarcoma cell culture, and histological sections of the Prussian blue stained rat kidney, liver and spleen. The result shows that our method is able to represent the color and shade as a numerical value that correlated well with human perception. © 2011 International Society for Advancement of Cytometry