Laser & Optoelectronics Progress, Volume. 62, Issue 18, 1817022(2025)
Deep Learning-Based Resolution Enhancement Method for NIR-II Fluorescence Imaging (Invited)
Fig. 1. NIR-II imaging system. (a) Schematic diagram of NIR-II fluorescence imaging system; (b) comparison of pixel size between NIR-II detector and visible light camera, and its impact on imaging quality, enlarged area is imaging effect of fine blood vessels under resolution constraint; (c) schematic diagram of Real-ESRGAN network architecture
Fig. 2. Performance comparison of different super-resolution methods in NIR-II mouse blood vascular imaging. (a) Evaluation process of model performance; (b) comparison of reconstruction results for mouse back blood vessels by different methods, lower areas are magnified details; (c) LPIPS and PIQE of different methods based on 160 test images
Fig. 3. Application of Real-ESRGAN in NIR-Ⅱc band imaging. (a) Original NIR-Ⅱc images and processing workflow in different scenarios; (b) high-resolution reconstruction results processed by different methods, lower area is magnified details, scale bar is 5 mm; (c) intensity distributions of multiple blood vessels
Fig. 4. Performance of Real-ESRGAN in clinical application of diabetic foot. (a) Clinical data acquisition process; (b) high-resolution foot blood vascular images processed by different methods, right area shows magnified details; (c) intensity distribution of multiple blood vessels
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Shiyi Peng, Yuhuang Zhang, Xiaolong Liu, Xiaoxiao Fan, Hui Lin, Jun Qian. Deep Learning-Based Resolution Enhancement Method for NIR-II Fluorescence Imaging (Invited)[J]. Laser & Optoelectronics Progress, 2025, 62(18): 1817022
Category: Medical Optics and Biotechnology
Received: May. 13, 2025
Accepted: Jun. 17, 2025
Published Online: Sep. 9, 2025
The Author Email: Jun Qian (qianjun@zju.edu.cn)
CSTR:32186.14.LOP251220