ArticleNpj imaging2025
Fast and label-free 3D virtual H&E histology via active phase modulation-assisted dynamic full-field OCT.
Article in Npj imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- High-resolution dynamic full-field optical coherence microscopy: illuminating intracellular activity in deep tissue.Npj imaging · 2026Article
- Virtual histology imaging of lymph nodesCancer biology & medicine · 2026Observational
- Advances and Opportunities in NIR-II Endoscopy: From Diagnosis to Therapeutic Applications.Diagnostics (Basel, Switzerland) · 2026Review
- Continuous scanning full-field OCT for fast volumetric imaging of multi-cellular aggregates.Biomedical optics express · 2026Article
- Article
- Dynamic optical coherence tomography algorithm for label-free assessment of swiftness and occupancy of intratissue moving scatterers.Biomedical optics express · 2026Article
- Visible Light Optical Coherence Tomography: Technology and Biomedical Applications.Bioengineering (Basel, Switzerland) · 2025Review
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Authors and funding
13 authors.
Funding
Abstract
Pathological features are the gold standard for tumor diagnosis, guiding treatment and prognosis. However, the standard histopathological process is labor-intensive and time-consuming. Although frozen sections offer a quicker alternative, they often induce severe artifacts and suffer from lower accuracy. Dynamic full-field optical coherence tomography (D-FFOCT) is an innovative optical imaging technique that provides rapid histological information by utilizing subcellular dynamics as an intrinsic source of contrast. Despite its advantages, D-FFOCT images of adjacent tissues frequently exhibit abrupt shifts in hue and brightness, which is confusing for pathologists and diminishes its interpretability and reliability. Here, we present an active phase modulation-assisted D-FFOCT (APMD-FFOCT) to improve the imaging stability and achieve continuity and consistency in image stitching, which also enhances the image contrast of tissues with low metabolic dynamics. This enables us to further employ an unsupervised generative adversarial network to convert APMD-FFOCT images into virtual hematoxylin and eosin (H&E) stained images for the first time. Three-dimensional (3D) virtual H&E-stained images can be obtained at a scanning rate of 1 frame per second. Furthermore, we also demonstrate that this novel technique has been successfully applied in cancer diagnosis for the human central nervous system and breast, which proves that this new method will play a new unique and important role in intraoperative histology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.