South Fredrick A, Kurokawa Kazuhiro, Liu Zhuolin, Liu Yuan-Zhi, Miller Donald T, Boppart Stephen A
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
Biomed Opt Express. 2018 May 8;9(6):2562-2574. doi: 10.1364/BOE.9.002562. eCollection 2018 Jun 1.
In many optical imaging applications, it is necessary to overcome aberrations to obtain high-resolution images. Aberration correction can be performed by either physically modifying the optical wavefront using hardware components, or by modifying the wavefront during image reconstruction using computational imaging. Here we address a longstanding issue in computational imaging: photons that are not collected cannot be corrected. This severely restricts the applications of computational wavefront correction. Additionally, performance limitations of hardware wavefront correction leave many aberrations uncorrected. We combine hardware and computational correction to address the shortcomings of each method. Coherent optical backscattering data is collected using high-speed optical coherence tomography, with aberrations corrected at the time of acquisition using a wavefront sensor and deformable mirror to maximize photon collection. Remaining aberrations are corrected by digitally modifying the coherently-measured wavefront during imaging reconstruction. This strategy obtains high-resolution images with improved signal-to-noise ratio of human photoreceptor cells with more complete correction of ocular aberrations, and increased flexibility to image at multiple retinal depths, field locations, and time points. While our approach is not restricted to retinal imaging, this application is one of the most challenging for computational imaging due to the large aberrations of the dilated pupil, time-varying aberrations, and unavoidable eye motion. In contrast with previous computational imaging work, we have imaged single photoreceptors and their waveguide modes in fully dilated eyes with a single acquisition. Combined hardware and computational wavefront correction improves the image sharpness of existing adaptive optics systems, and broadens the potential applications of computational imaging methods.
在许多光学成像应用中,有必要克服像差以获得高分辨率图像。像差校正可以通过使用硬件组件对光波前进行物理修改来实现,也可以在图像重建过程中使用计算成像来修改波前。在这里,我们解决了计算成像中一个长期存在的问题:未被收集的光子无法被校正。这严重限制了计算波前校正的应用。此外,硬件波前校正的性能限制使得许多像差无法得到校正。我们将硬件和计算校正相结合,以解决每种方法的缺点。使用高速光学相干断层扫描收集相干光学背散射数据,在采集时使用波前传感器和可变形镜校正像差,以最大限度地收集光子。剩余的像差通过在成像重建过程中对相干测量的波前进行数字修改来校正。这种策略能够获得高分辨率图像,提高了人类光感受器细胞的信噪比,更全面地校正了眼像差,并且在多个视网膜深度、视野位置和时间点进行成像时具有更高的灵活性。虽然我们的方法不限于视网膜成像,但由于散瞳的大像差、时变像差和不可避免的眼球运动,该应用是计算成像中最具挑战性的应用之一。与之前的计算成像工作相比,我们通过单次采集对完全散瞳的眼睛中的单个光感受器及其波导模式进行了成像。硬件和计算波前校正相结合提高了现有自适应光学系统的图像清晰度,并拓宽了计算成像方法的潜在应用。