Stain Removal Through Color Normalization of Haematoxylin and Eosin Images: A Review

Abstract

Abstract Histopathology images are used for the diagnosis and examination of cancer cells. Preparing and scanning histopathology slides consist of numerous steps of which staining are an important process. But these staining procedures cause multitude problems as there may be variations in the slides due to multiple reasons. Color variations in histopathology images can occur due to inconsistent staining of biopsy tissue, color responses of different scanners or difference in raw materials and manufacturing techniques used by stain. These factors hamper the generalization of automatic image analysis method. Hence there is a need for standardizing the image before analysis by performing stain normalization which is achieved by removing the stains for visual enhancement. Color normalization techniques play a vital in the developing computerized decision support system. In this paper, a detailed study and performance evaluation of various color normalization techniques such as Histogram Specification, Macenko Method, Reinhard Method on histopathology images are presented. In these normalization procedures the mean color of the target image is transferred onto the source image. Quality performance of different stain normalization techniques is evaluated based on Entropy and Structure Similarity Index Measure (SSIM). In this work, we record the time complexity of the color normalization algorithms. The normalization techniques are tested on histopathological images from UCSB dataset and Mitosis Atypia 2014 dataset. This article reviews and summarizes the color normalization techniques on histopathological images for visual improvement.