Log In Sign Up

Pix2Pix-based Stain-to-Stain Translation: A Solution for Robust Stain Normalization in Histopathology Images Analysis

by   Pegah Salehi, et al.

The diagnosis of cancer is mainly performed by visual analysis of the pathologists, through examining the morphology of the tissue slices and the spatial arrangement of the cells. If the microscopic image of a specimen is not stained, it will look colorless and textured. Therefore, chemical staining is required to create contrast and help identify specific tissue components. During tissue preparation due to differences in chemicals, scanners, cutting thicknesses, and laboratory protocols, similar tissues are usually varied significantly in appearance. This diversity in staining, in addition to Interpretive disparity among pathologists more is one of the main challenges in designing robust and flexible systems for automated analysis. To address the staining color variations, several methods for normalizing stain have been proposed. In our proposed method, a Stain-to-Stain Translation (STST) approach is used to stain normalization for Hematoxylin and Eosin (H E) stained histopathology images, which learns not only the specific color distribution but also the preserves corresponding histopathological pattern. We perform the process of translation based on the pix2pix framework, which uses the conditional generator adversarial networks (cGANs). Our approach showed excellent results, both mathematically and experimentally against the state of the art methods. We have made the source code publicly available.


page 1

page 3

page 5

page 6


GAN-based Virtual Re-Staining: A Promising Solution for Whole Slide Image Analysis

Histopathological cancer diagnosis is based on visual examination of sta...

Multimarginal Wasserstein Barycenter for Stain Normalization and Augmentation

Variations in hematoxylin and eosin (H E) stained images (due to clini...

A Morphology Focused Diffusion Probabilistic Model for Synthesis of Histopathology Images

Visual microscopic study of diseased tissue by pathologists has been the...

Whole-Sample Mapping of Cancerous and Benign Tissue Properties

Structural and mechanical differences between cancerous and healthy tiss...

Stain Style Transfer using Transitive Adversarial Networks

Digitized pathological diagnosis has been in increasing demand recently....

Context-based Normalization of Histological Stains using Deep Convolutional Features

While human observers are able to cope with variations in color and appe...