ReviewLasers in surgery and medicine2021
Deep Learning in Biomedical Optics.
Review in Lasers in surgery and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
32 citing papers in PubMed.
- Artificial Second Harmonic Generation Image Feature Tuning with Generative Models and SeFa Semantic Analysis.JPhys photonics · 2026Article
- Validation of an automated AI-based micro-CT organ segmentation workflow against expert annotations and its impact on fluorescence quantification.European radiology experimental · 2026Article
- Deep Learning Integration in Optical Microscopy: Advancements and Applications.Microscopy research and technique · 2026Review
- Autofluorescence and deep learning in early disease detection: biological foundations, clinical applications, and future directions.Frontiers in artificial intelligence · 2026Review
- Deep Learning to Localize Photoacoustic Sources in Three Dimensions: Theory and Implementation.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2025Article
- Persistent homology-based optical properties of microscopic turbid media for realistic light propagation analysis.Biomedical optics express · 2025Article
- Focal adhesion in the tumour metastasis: from molecular mechanisms to therapeutic targets.Biomarker research · 2025Review
- Ultra-sparse reconstruction for photoacoustic tomography: Sinogram domain prior-guided method exploiting enhanced score-based diffusion model.Photoacoustics · 2025Article
- Deep learning-enabled fluorescence imaging for surgical guidance:Journal of biomedical optics · 2025Article
- Deep learning-based temporal deconvolution for photon time-of-flight distribution retrieval.Optics letters · 2024Article
- Neural network-based processing and reconstruction of compromised biophotonic image data.Light, science & applications · 2024Review
- U-Net enhanced real-time LED-based photoacoustic imaging.Journal of biophotonics · 2024Article
- Advancements in fluorescence lifetime imaging microscopy Instrumentation: Towards high speed and 3D.Current opinion in solid state & materials science · 2024Article
- Self-Supervised Joint Learning for pCLE Image Denoising.Sensors (Basel, Switzerland) · 2024Article
- Applications of machine learning in time-domain fluorescence lifetime imaging: a review.Methods and applications in fluorescence · 2024Review
- Harnessing artificial intelligence to reduce phototoxicity in live imaging.Journal of cell science · 2024Article
- Artificial intelligence algorithms for real-time detection of colorectal polyps during colonoscopy: a review.American journal of cancer research · 2024Review
- Model-Based Explainable Deep Learning for Light-Field Microscopy Imaging.IEEE transactions on image processing : a publication of the IEEE Signal Processing Society · 2024Article
- Deep learningJournal of biomedical optics · 2024Article
- Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo microscopy, widefield endoscopy, optical coherence tomography, photoacoustic imaging, diffuse tomography, and functional optical brain imaging. For each of these domains, we summarize how deep learning has been applied and highlight methods by which deep learning can enable new capabilities for optics in medicine. Challenges and opportunities to improve translation and adoption of deep learning in biomedical optics are also summarized. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.
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What OpenQuestion holds
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.