ArticleProceedings of the National Academy of Sciences of the United States of America2020
Deep learning extended depth-of-field microscope for fast and slide-free histology.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed, 80 citations in OpenAlex.
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- Multispectral extended depth-of-field fluorescence microscopy with co-designed meta-optics and neural reconstruction.Light, science & applications · 2026Article
- Deep-learning endomicroscope with large field-of-view and depth-of-field for real-time in vivo imaging of epithelial cancer hallmarks.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Digital defocus aberration interference for automated optical microscopy.Nature communications · 2026Article
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- Dual-Channel Event Microscopy for Ultrafast Biological Imaging.bioRxiv : the preprint server for biology · 2025Article
- Multiplane 2.5D microscopy for high-throughput high-resolution tissue imaging.Journal of biomedical optics · 2025Article
- Emerging Trends in Point-of-Care Technology Development for Oncology in Low- and Middle-Income Countries.JCO global oncology · 2025Review
- Label-free optical microscopy with artificial intelligence: a new paradigm in pathology.Biophotonics discovery · 2025Review
- Deep learning-enabled filter-free fluorescence microscope.Science advances · 2025Article
- Machine Learning and Deep Learning Applications in Magnetic Particle Imaging.Journal of magnetic resonance imaging : JMRI · 2025Review
- Overcoming photon and spatiotemporal sparsity in fluorescence lifetime imaging with SparseFLIM.Communications biology · 2024Article
- Highly sensitive volumetric single-molecule imaging.Nanophotonics (Berlin, Germany) · 2024Article
- Multi-Focus Images Fusion for Fluorescence Imaging Based on Local Maximum Luminosity and Intensity Variance.Sensors (Basel, Switzerland) · 2024Article
- DeepDOF-SE: affordable deep-learning microscopy platform for slide-free histology.Nature communications · 2024Article
- Optical imaging for screening and early cancer diagnosis in low-resource settings.Nature reviews bioengineering · 2024Article
- Optical imaging technologies forCurrent opinion in biomedical engineering · 2023Article
- Generalizations of the Jaccard index and Sørensen index for assessing agreement across multiple readers in object detection and instance segmentation in biomedical imaging.Journal of medical imaging (Bellingham, Wash.) · 2023Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field (DOF), resected tissue is either frozen or preserved with chemical fixatives, sliced into thin sections placed on microscope slides, stained, and imaged to determine whether surgical margins are free of tumor cells-a costly and time- and labor-intensive procedure. Here, we introduce a deep-learning extended DOF (DeepDOF) microscope to quickly image large areas of freshly resected tissue to provide histologic-quality images of surgical margins without physical sectioning. The DeepDOF microscope consists of a conventional fluorescence microscope with the simple addition of an inexpensive (less than $10) phase mask inserted in the pupil plane to encode the light field and enhance the depth-invariance of the point-spread function. When used with a jointly optimized image-reconstruction algorithm, diffraction-limited optical performance to resolve subcellular features can be maintained while significantly extending the DOF (200 µm). Data from resected oral surgical specimens show that the DeepDOF microscope can consistently visualize nuclear morphology and other important diagnostic features across highly irregular resected tissue surfaces without serial refocusing. With the capability to quickly scan intact samples with subcellular detail, the DeepDOF microscope can improve tissue sampling during intraoperative tumor-margin assessment, while offering an affordable tool to provide histological information from resected tissue specimens in resource-limited settings.
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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.