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13 March 2024 Label-free coded aperture snapshot spectral imaging fundus camera
Ruixuan Zhao, Chengshuai Yang, R. Theodore Smith, Liang Gao
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Proceedings Volume PC12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences; PC1285708 (2024) https://doi.org/10.1117/12.3000741
Event: SPIE BiOS, 2024, San Francisco, California, United States
Abstract
Spectral imaging holds great promise for the non-invasive diagnosis of retinal diseases. However, to acquire a spectral datacube, conventional spectral cameras require extensive scanning, leading to a prolonged acquisition. Therefore, they are inapplicable to retinal imaging because of the rapid eye movement. To address this problem, we built a coded aperture snapshot spectral imaging fundus camera, which captures a large-sized spectral datacube in a single exposure. Moreover, to reconstruct a high-resolution image, we developed a robust deep unfolding algorithm using a state-of-the-art spectral transformer in the denoising network. We demonstrated the performance of the system through various experiments, including imaging standard targets, utilizing an eye phantom, and conducting in vivo imaging of the human retina.
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Ruixuan Zhao, Chengshuai Yang, R. Theodore Smith, and Liang Gao "Label-free coded aperture snapshot spectral imaging fundus camera", Proc. SPIE PC12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences, PC1285708 (13 March 2024); https://doi.org/10.1117/12.3000741
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KEYWORDS
Cameras
Coded apertures
Imaging spectroscopy
Spectral imaging cameras
Imaging systems
Image restoration
Optical coherence tomography
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