Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue

01/20/2020
by   Yijie Zhang, et al.
5

Histological staining is a vital step used to diagnose various diseases and has been used for more than a century to provide contrast to tissue sections, rendering the tissue constituents visible for microscopic analysis by medical experts. However, this process is time-consuming, labor-intensive, expensive and destructive to the specimen. Recently, the ability to virtually-stain unlabeled tissue sections, entirely avoiding the histochemical staining step, has been demonstrated using tissue-stain specific deep neural networks. Here, we present a new deep learning-based framework which generates virtually-stained images using label-free tissue, where different stains are merged following a micro-structure map defined by the user. This approach uses a single deep neural network that receives two different sources of information at its input: (1) autofluorescence images of the label-free tissue sample, and (2) a digital staining matrix which represents the desired microscopic map of different stains to be virtually generated at the same tissue section. This digital staining matrix is also used to virtually blend existing stains, digitally synthesizing new histological stains. We trained and blindly tested this virtual-staining network using unlabeled kidney tissue sections to generate micro-structured combinations of Hematoxylin and Eosin (H E), Jones silver stain, and Masson's Trichrome stain. Using a single network, this approach multiplexes virtual staining of label-free tissue with multiple types of stains and paves the way for synthesizing new digital histological stains that can be created on the same tissue cross-section, which is currently not feasible with standard histochemical staining methods.

READ FULL TEXT

Authors

page 13

page 14

page 15

page 16

page 17

page 18

page 19

03/30/2018

Deep learning-based virtual histology staining using auto-fluorescence of label-free tissue

Histological analysis of tissue samples is one of the most widely used m...
10/15/2018

Virtualization of tissue staining in digital pathology using an unsupervised deep learning approach

Histopathological evaluation of tissue samples is a key practice in pati...
12/08/2021

Label-free virtual HER2 immunohistochemical staining of breast tissue using deep learning

The immunohistochemical (IHC) staining of the human epidermal growth fac...
10/17/2018

Strategies for Training Stain Invariant CNNs

An important part of Digital Pathology is the analysis of multiple digit...
03/14/2020

Rapid Whole Slide Imaging via Learning-based Two-shot Virtual Autofocusing

Whole slide imaging (WSI) is an emerging technology for digital patholog...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.