Journal of biomedical optics · 2026
Development and validation of a high-resolution hyperspectral imaging system for the retina.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Tran Minh H, Pruitt Kelden, Bryarly Michelle, Emordi Isioma, Ali Arrsh, Ma Ling, Fei Baowei
Аннотация
SIGNIFICANCE: Early detection of Alzheimer's diseases, diabetic retinopathy, or macular degeneration with advanced retinal imaging technologies can help improve patient care and treatment outcome.
AIM: We aim to create a high-resolution hyperspectral imaging (HSI) system for the retina. Retinal vessel diameter and oxygenation rate will be extracted simultaneously from HSI data.
APPROACH: Our hyperspectral retinal imaging system consists of a snapshot hyperspectral camera, a high-resolution RGB camera, a beamsplitter, and an imaging endoscope. Multiple pansharpening algorithms, including deep learning methods, were developed to generate high-resolution hyperspectral images that were further used for the measurement of vessel size and oxygenation rate in mice.
RESULTS: The hyperspectral retinal imaging system was tested for its spatial resolution and spectral fidelity in retina phantoms. In vivo imaging experiments were performed in mice. The deep learning-based pansharpening algorithm achieved a root mean square error (RMSE) of 2.15 ± 0.64 , a correlation coefficient (CC) of 0.96 ± 0.05 , a spectral angle score of 0.06 ± 0.03 radians, and an error relative global dimensionless synthesis (ERGAS) score of 2.37 ± 1.71 . Oxygen saturation ( sO 2 ) and lumen diameters of blood vessels were measured in the retina. The average lumen diameter of the venules was 45.7 ± 13.6 μ m , whereas the average lumen diameter of the arterioles was 31.5 ± 8.7 μ m . The average arteriole sO 2 was 98%, whereas the average venule sO 2 was 58%.
CONCLUSIONS: A high-resolution hyperspectral imaging system was developed and validated for retina imaging and measurement of blood vessels and oxygen saturation.
AIM: We aim to create a high-resolution hyperspectral imaging (HSI) system for the retina. Retinal vessel diameter and oxygenation rate will be extracted simultaneously from HSI data.
APPROACH: Our hyperspectral retinal imaging system consists of a snapshot hyperspectral camera, a high-resolution RGB camera, a beamsplitter, and an imaging endoscope. Multiple pansharpening algorithms, including deep learning methods, were developed to generate high-resolution hyperspectral images that were further used for the measurement of vessel size and oxygenation rate in mice.
RESULTS: The hyperspectral retinal imaging system was tested for its spatial resolution and spectral fidelity in retina phantoms. In vivo imaging experiments were performed in mice. The deep learning-based pansharpening algorithm achieved a root mean square error (RMSE) of 2.15 ± 0.64 , a correlation coefficient (CC) of 0.96 ± 0.05 , a spectral angle score of 0.06 ± 0.03 radians, and an error relative global dimensionless synthesis (ERGAS) score of 2.37 ± 1.71 . Oxygen saturation ( sO 2 ) and lumen diameters of blood vessels were measured in the retina. The average lumen diameter of the venules was 45.7 ± 13.6 μ m , whereas the average lumen diameter of the arterioles was 31.5 ± 8.7 μ m . The average arteriole sO 2 was 98%, whereas the average venule sO 2 was 58%.
CONCLUSIONS: A high-resolution hyperspectral imaging system was developed and validated for retina imaging and measurement of blood vessels and oxygen saturation.