Deep Learning Enhanced NIR-II Volume Images

New issue from Advances in optoelectronics, 10.29026/oea. 2023.220105 discusses deep learning-enhanced NIR-II volumetric imaging of the entire mouse vasculature.

In vivo small animal fluorescence imaging can be used for in vivo real-time imaging observations of labeled animal tissues and exogenous drugs. This system enables long-term tracking of tumor growth, metastasis, drug treatment process, infectious disease development process, inflammation and repair of bone damage, specific gene expression process, metabolism, etc. in living animals. increase. Nanomedicine processes in living organisms. This system is also an imaging platform for the design and optimization of various fluorophores and biological probes.

Near-infrared II (NIR-II: 1000-1700 nm) are photons with longer wavelengths than visible light and NIR-I light. Less scattering within living tissue and less background interference from tissue autofluorescence. With the development of NIR-II photoluminescence probes and supporting cameras and other instruments, the application of NIR-II fluorescence in vivo functional imaging has become a research hotspot. However, his current NIR-II in vivo imaging system is based on planar imaging obtained with industrial lenses and can acquire millimeter-depth fluorescence imaging, but cannot reflect three-dimensional depth information. Additionally, the mouse is further away from the lens and the imaging resolution is lower. Tissue scattering effects are still present. Therefore, the development of deep, high-resolution, spatial three-dimensional, and high-contrast in vivo imaging systems has become an important development direction for small animal in vivo fluorescence imaging.

Light-sheet fluorescence microscopy imaging is a three-dimensional imaging technique applied to cells, organoids, and small embryos, enabling rapid three-dimensional imaging of biological samples. To achieve deep 3D in vivo imaging with NIR-II fluorescence, improve imaging resolution, and reduce the effects of fluorescence scattering and tissue autofluorescence, a team led by Southern University of Science and Technology scholar Dayong Jin Prepared the NIR-II probe. Use rare earth nanoparticles to detect fluorescence with a peak around 1530 nm. They were the first to introduce light sheet imaging into the field of in vivo imaging of whole adult mice. The team used a time-gating technique to reduce thermal effects and average laser power. They also expanded the imaging numerical aperture by combining imaging with dual industrial lenses (see Figure 1) and developed a deep learning-based vessel enhancement algorithm to improve imaging contrast. These advances enabled high-resolution whole mouse vascular network imaging with deep 3D in vivo imaging in the NIR-II region (see Figure 2).

In this study, we used NIR-II body imaging to achieve distinct resolution of blood vessels in deep tissue by synergistically using time-gated imaging, light sheet scanning, and deep learning algorithms. These techniques effectively reduced the effects of laser scattering and out-of-focus background noise. The 3D in vivo imaging system successfully reconstructed a total vessel length of 527.7 mm with a depth range of 2 mm under the gross mouse skin. The smallest resolvable vessel diameter was up to 100 µm and the depth resolution was 100 µm. This technique bridges the gap between conventional microscopic and macroscopic imaging and offers the potential for 3D systemic pathology model studies. The system rapidly acquires vast amounts of information and can analyze microscopic details of macroscopic regions of interest, such as cancer cell trafficking processes in blood vessels, in the full human context. A new generation of his NIR-II 3D in vivo deep HD imaging offers significant advantages over current tissue clearing techniques used to avoid scattering effects.

keyword: NIR-II fluorescence / time gating / light sheet illumination / deep learning / vessel enhancement / 3D imaging

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In early 2019, Academician Jin Dayong established the Joint Research Center for Materials and Instruments in Biomedical Sciences, Sydney University of Science and Technology – Southern University of Science and Technology, dedicated to the development of advanced biomedical technology. We focus on the design of new materials, the self-development of medical devices, and the integration of precision disease diagnostic technology. Over the past five years, Dr. Jin has published 16 original reviews in Nature and its subjournals as corresponding author, and to date he has published over 220 scientific papers with over 11,000 citations and citations. achieving his H-Index of 52. He was invited to present at many international conferences such as SPIE, CYTO. He has served as associate editor of many international journals such as Light Science & Applications (his second in Optics), Cytometry A, Journal of Luminescence, Opto-Electronic Advances. , Journal of Rare Earths and Science China Materials, Nature, Nature Photonics, Nature Nanotechnology, Nature Communication, Chemical Society Reviews, Scientific Reports, Advanced Materials, Advanced Functional Materials, Nano Letters, ACS Nano, Journal of Biomedical Optics, Optics Letters, Small , Nanoscale, Chemical Science, etc. Reviewer for Analytical Chemistry and other journals.

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Advances in optoelectronics (OEA) is an influential open access, peer-reviewed monthly SCI journal with an Impact Factor of 8.933 (Journal Citation Reports for IF2021). Since its launch in March 2018, OEA has been indexed in the SCI, EI, DOAJ, Scopus, CA and ICI databases and its editorial board has expanded from 17 countries and territories to his 36 members. (mean h-index 49).

The journal aims to provide a platform for researchers, scholars, professionals, practitioners, and students to communicate and share knowledge in the form of high-quality empirical and theoretical research papers. Published by Optoelectronics Laboratory. Topics of optics, photonics and optoelectronics.

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article reference Wu ST, Yang ZC, Ma CG, Zhang X, Mi C et al. Deep learning enhanced NIR-II volumetric imaging of the entire mouse vasculature. optoelectronic advance 6, 220105 (2023). Doi: 10.29026/oea.2023.220105

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