Comparison of deep learning models for digital H&E staining from unpaired label-free multispectral microscopy images.
Journal:
Computer methods and programs in biomedicine
Published Date:
Apr 5, 2023
Abstract
BACKGROUND AND OBJECTIVE: This paper presents the quantitative comparison of three generative models of digital staining, also known as virtual staining, in H&E modality (i.e., Hematoxylin and Eosin) that are applied to 5 types of breast tissue. Moreover, a qualitative evaluation of the results achieved with the best model was carried out. This process is based on images of samples without staining captured by a multispectral microscope with previous dimensional reduction to three channels in the RGB range.