# Virtual birefringence imaging and histological staining of amyloid deposits in label-free tissue using autofluorescence microscopy and deep learning

arXiv: https://arxiv.org/abs/2403.09100 · HTML: https://mlsanity.com/paper/2403.09100/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 85 references that are in the map.
- First posted on arXiv 14 Mar 2024.

## Builds on (most cited first, 19 of 19)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [PyTorch: An Imperative Style, High-Performance Deep Learning Library](https://mlsanity.com/paper/1912.01703/) (2019)
- [Conditional Generative Adversarial Nets](https://mlsanity.com/paper/1411.1784/) (2014)
- [Attention U-Net: Learning Where to Look for the Pancreas](https://mlsanity.com/paper/1804.03999/) (2018)
- [VoxelMorph: A Learning Framework for Deformable Medical Image Registration](https://mlsanity.com/paper/1809.05231/) (2018)
- [Artificial Intelligence for Digital and Computational Pathology](https://mlsanity.com/paper/2401.06148/) (2023)
- [Breaking the Dilemma of Medical Image-to-image Translation](https://mlsanity.com/paper/2110.06465/) (2021)
- [Deep learning-based virtual histology staining using auto-fluorescence of label-free tissue](https://mlsanity.com/paper/1803.11293/) (2018)
- [Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation](https://mlsanity.com/paper/2003.08073/) (2020)
- [Deep learning-based transformation of the H&E stain into special stains](https://mlsanity.com/paper/2008.08871/) (2020)
- [Deep Learning-enabled Virtual Histological Staining of Biological Samples](https://mlsanity.com/paper/2211.06822/) (2022)
- [PhaseStain: Digital staining of label-free quantitative phase microscopy images using deep learning](https://mlsanity.com/paper/1807.07701/) (2018)
- [Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue](https://mlsanity.com/paper/2001.07267/) (2020)
- [Label-free virtual HER2 immunohistochemical staining of breast tissue using deep learning](https://mlsanity.com/paper/2112.05240/) (2021)
- [Virtual stain transfer in histology via cascaded deep neural networks](https://mlsanity.com/paper/2207.06578/) (2022)
- [Virtual staining of defocused autofluorescence images of unlabeled tissue using deep neural networks](https://mlsanity.com/paper/2207.02946/) (2022)
- [Virtual histological staining of unlabeled autopsy tissue](https://mlsanity.com/paper/2308.00920/) (2023)
- [Digital staining in optical microscopy using deep learning -- a review](https://mlsanity.com/paper/2303.08140/) (2023)
- [A comparative evaluation of image-to-image translation methods for stain transfer in histopathology](https://mlsanity.com/paper/2303.17009/) (2023)

## Built on by (most cited first, 8 of 8)

- [Pixel super-resolved virtual staining of label-free tissue using diffusion models](https://mlsanity.com/paper/2410.20073/) (2024)
- [Virtual Staining of Label-Free Tissue in Imaging Mass Spectrometry](https://mlsanity.com/paper/2411.13120/) (2024)
- [Label-free evaluation of lung and heart transplant biopsies using tissue autofluorescence-based virtual staining](https://mlsanity.com/paper/2409.05255/) (2024)
- [Deep learning-enabled virtual multiplexed immunostaining of label-free tissue for vascular invasion assessment](https://mlsanity.com/paper/2508.16209/) (2025)
- [Virtual Gram staining of label-free bacteria using darkfield microscopy and deep learning](https://mlsanity.com/paper/2407.12337/) (2024)
- [IMPLICITSTAINER: Resolution Agnostic Data-Efficient Virtual Staining Using Neural Implicit Functions](https://mlsanity.com/paper/2505.09831/) (2025)
- [Building Trust in Virtual Immunohistochemistry: Automated Assessment of Image Quality](https://mlsanity.com/paper/2511.04615/) (2025)
- [Autonomous labeling of surgical resection margins using a foundation model](https://mlsanity.com/paper/2511.22131/) (2025)

## Abstract (arXiv)

Systemic amyloidosis is a group of diseases characterized by the deposition of misfolded proteins in various organs and tissues, leading to progressive organ dysfunction and failure. Congo red stain is the gold standard chemical stain for the visualization of amyloid deposits in tissue sections, as it forms complexes with the misfolded proteins and shows a birefringence pattern under polarized light microscopy. However, Congo red staining is tedious and costly to perform, and prone to false diagnoses due to variations in the amount of amyloid, staining quality and expert interpretation through manual examination of tissue under a polarization microscope. Here, we report the first demonstration of virtual birefringence imaging and virtual Congo red staining of label-free human tissue to show that a single trained neural network can rapidly transform autofluorescence images of label-free tissue sections into brightfield and polarized light microscopy equivalent images, matching the histochemically stained versions of the same samples. We demonstrate the efficacy of our method with blind testing and pathologist evaluations on cardiac tissue where the virtually stained images agreed well with the histochemically stained ground truth images. Our virtually stained polarization and brightfield images highlight amyloid birefringence patterns in a consistent, reproducible manner while mitigating diagnostic challenges due to variations in the quality of chemical staining and manual imaging processes as part of the clinical workflow.