Deep learning for in vivo near-infrared imaging
Open accessAbstract
Significance: Near-infrared (NIR) fluorescence imaging using biocompatible dyes such as ICG in the NIR-I (800–1,000 nm) has facilitated tumor imaging and imaging-guided surgery, but suffers from shallow imaging depth, low contrast, and poor clarity caused by light scattering and autofluorescence. On the other hand, fluorescence imaging in NIR-IIb (1,500–1,700 nm) affords much improved spatial resolution and deeper tissue penetration, but currently relies on fluorophores not approved for human use. This work presents a deep-learning–based approach to transform a blurred NIR-I image to a much higher-clarity image like in NIR-IIb, leading to an image closely resembling the ground truth. The deep-learning–enabled high-resolution NIR imaging could facilitate basic biomedical research and empower diagnostics and imaging-guided surgery in the clinic.
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Image analysis using deep neural networks can partially address the limited spatial resolution by transforming a blurred image to a much higher-clarity image closely resembling the ground truth.
“This can be partially addressed by applying an image analysis using deep neural networks to transform a blurred image to a much higher-clarity image closely resembling the ground truth.198,199”
From The Pursuit of Shortwave Infrared-Emitting Nanoparticles with Bright Fluorescence through Molecular Design and Excited-State Engineering of Molecular Aggregates (2022) · cites this paper as [198]
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“198,199 5.1.2.”
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- Authors
- Ma, Z., Wang, F., Wang, W., Zhong, Y., & Dai, H.
- Affiliations
- Stanford University (US)
- Corresponding author
- Dai, Hongjie
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2020-12-28
- Volume
- 118
- Issue
- 1
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC7817119
- OpenAlex
- W3115300508
- Cited by
- 135
- References
- 55
- Citations by year
- 2026: 26 · 2025: 31 · 2024: 29 · 2023: 22 · 2022: 18 · 2021: 9
- FWCI
- 5.97
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- HHS | National Institutes of Health (DP1-NS-105737)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
- Keywords
- NIR-II fluorescence imaging, indocyanine green, lymph node imaging, PD-L1, EGFR, light-sheet microscopy, light scattering, small-molecule fluorescent probes, image-guided surgery
- MeSH terms
- Cetuximab, Intravital Microscopy, Deep Learning, Animals, Fluorescent Dyes, Humans, Indocyanine Green, Indoles, Lymph Nodes, Mice, Inbred BALB C, Mice, Nude, Microscopy, Fluorescence, Neoplasms, Neural Networks, Computer, Spectroscopy, Near-Infrared, Cell Line, Tumor, Mice, Molecular Imaging, Signal-To-Noise Ratio
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