Zhao Ruixuan, Yang Chengshuai, Gao Liang
Department of Bioengineering, University of California Los Angeles, Los Angeles, CA 90095, USA.
Res Sq. 2023 May 10:rs.3.rs-2515559. doi: 10.21203/rs.3.rs-2515559/v1.
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 system performance on both standard targets and an eye phantom.
光谱成像在视网膜疾病的非侵入性诊断方面具有巨大潜力。然而,为了获取光谱数据立方体,传统光谱相机需要进行大量扫描,导致采集时间延长。因此,由于眼球快速运动,它们不适用于视网膜成像。为了解决这个问题,我们构建了一种编码孔径快照光谱成像眼底相机,它可以在单次曝光中捕获大尺寸光谱数据立方体。此外,为了重建高分辨率图像,我们在去噪网络中使用了先进的光谱变换器开发了一种强大的深度展开算法。我们在标准目标和眼部模型上展示了该系统的性能。