Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong.
Cytometry A. 2011 Apr;79(4):311-6. doi: 10.1002/cyto.a.21037. Epub 2011 Mar 8.
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.
染色图像的颜色和色调的客观评估仍然没有得到解决，并且在生物医学研究中经常广泛遇到。目前，大多数对染色图像的颜色和色调的评估都是通过主观分级来进行的，这种方法容易受到读者间差异的影响。本文提出了一种新的方法，基于染色组织学图像在 CIELAB 颜色空间中的相似性图，根据用户指定的参考颜色，自动量化染色图像的颜色和色调。该算法应用于三个数据集，即一个幻影图像、人骨肉瘤细胞培养的普鲁士蓝染色和普鲁士蓝染色的大鼠肾、肝和脾组织切片。结果表明，我们的方法能够用一个与人类感知相关的数值来表示颜色和色调。
