Digital separation of diaminobenzidine-stained tissues via an automatic color-filtering for immunohistochemical quantification

The digital separation of diaminobenzidine (DAB)-stained tissues from hematoxylin background is an important pre-processing step to analyze immunostains. In most stain separation methods, specific color channels (for example: RGB, HSI, CMYK) or color deconvolution matrices are used to obtain different tissue contrasts between DAB- and hematoxylinstained areas. However, these methods could produce incomplete separation or color changes because the color spectra of stains and co-localized stains overlap in histological images. Therefore, we proposed an automatic colorfiltering to separate hematoxylin- and DAB-stained tissues. In implantation, the RGB images of DAB-labeled immunostains are first converted to 8-bit BN images by a mathematical translation to produce the largest contrast between brown DAB-stained tissues and blue hematoxylin-stained tissues. The first valley in the histogram revised by nonuniform quantization is set as the cut-off point to obtain a brown filter. DAB-stained tissues are accurately delineated from the background counterstain, resulting in DAB-only-image and De-DAB-image. Subsequently, a blue filter is designed in the CIE-Lab color space to further delineate the hematoxylin-stained tissues from the De-DAB-image. Finally, the average values of the remaining pixels of the De-DAB-image are set as the background color of the DAB-only-image to manage uneven dyeing and provide DAB-stained-image for adaptive immunohistochemistry quantitation. Extensive experimental results demonstrated that the proposed method has significant advantages compared with existing methods in terms of complete stain separation without changing the color in DAB-stained areas.