Bendkowski, C; Levine, A P; Rodriguez-Justo, M; Lovat, L B; Novelli, M; Shaw, M (2025) VS-FPM: Large-Format, Label-Free Virtual Histopathology Microscopy. BME Frontiers, 6. 0206 ISSN 2765-8031

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Abstract

Objective: This article describes a new method (VS-FPM) for analysis of unstained tissues based on the application of supervised machine learning to generate brightfield hematoxylin and eosin (H&E) images from phase images recovered using Fourier ptychographic microscopy (FPM).

Impact Statement: VS-FPM has several advantages for label-free digital pathology. Capture of complex image information simplifies model training and allows post-capture refocusing. FPM images combine high resolution with a large field of view, and the hardware is low-cost and compatible with many existing brightfield microscope systems. Introduction: By generating realistic histologically stained images from label-free image data, virtual staining (VS) methods have the potential to streamline clinical workflows, improve image consistency, and enable new ways of visualizing and analyzing histological tissues.

Methods: We trained a conditional generative adversarial network to translate high-resolution FPM images of unstained tissues to brightfield H&E images and assessed the method using diagnosis of colonic polyps as a test case.

Results: We found no statistically significant difference between the spatial resolution of FPM images captured at 4× magnification and images from a pathology slide scanner at 20× magnification. Visual assessment and image similarity metrics showed that VS-FPM images of unstained tissues closely resemble images of chemically H&E-stained tissues. However, the spatial resolution of virtual H&E images was approximately 20% lower than equivalent images of chemically stained tissues. Using VS-FPM, board-certified pathologists were able to accurately distinguish normal from dysplastic tissues and derive correct pathological diagnoses.

Conclusion: VS-FPM is a reliable, accessible VS method that also overcomes many other limitations inherent to histopathology microscopy.

Item Type:	Article
Keywords:	Virtual staining, Fourier ptychography, histopathology, generative adversarial networks,computational microscopy, label-free microscopy, quantitative phase imaging, cancer diagnosis,colonic polyps
Subjects:	Biotechnology > Bio-Diagnostics
Divisions:	Chemical & Biological Sciences
Identification number/DOI:	10.34133/bmef.0206
Last Modified:	09 Jun 2026 12:49
URI:	https://eprintspublications.npl.co.uk/id/eprint/10423