Vision Science and Advanced Retinal Imaging Laboratory (VSRI), Department of Ophthalmology and Vision Science, UC Davis Eye Center, Sacramento, CA, United States of America.
Department of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Torun, Poland.
PLoS One. 2018 Oct 25;13(10):e0206052. doi: 10.1371/journal.pone.0206052. eCollection 2018.
In retinal raster imaging modalities, fixational eye movements manifest as image warp, where the relative positions of the beam and retina change during the acquisition of single frames. To remove warp artifacts, strip-based registration methods-in which fast-axis strips from target images are registered to a reference frame-have been applied in adaptive optics (AO) scanning light ophthalmoscopy (SLO) and optical coherence tomography (OCT). This approach has enabled object tracking and frame averaging, and methods have been described to automatically select reference frames with minimal motion. However, inconspicuous motion artifacts may persist in reference frames and propagate themselves throughout the processes of registration, tracking, and averaging. Here we test a previously proposed method for removing movement artifacts in reference frames, using biases in stripwise cross-correlation statistics. We applied the method to synthetic retinal images with simulated eye motion artifacts as well as real AO-SLO images of the cone mosaic and volumetric AO-OCT images, both affected by eye motion. In the case of synthetic images, the method was validated by direct comparison with motion-free versions of the images. In the case of real AO images, performance was validated by comparing the correlation of uncorrected images with that of corrected images, by quantifying the effect of motion artifacts on the image power spectra, and by qualitative examination of AO-OCT B-scans and en face projections. In all cases, the proposed method reduced motion artifacts and produced more faithful images of the retina.
在视网膜光栅成象模态中，固视眼动表现为图像扭曲，即在采集单帧图像期间光束和视网膜的相对位置发生变化。为了去除扭曲伪影，基于条带的配准方法——其中目标图像的快轴条带被配准到参考帧——已应用于自适应光学（AO）扫描激光检眼镜（SLO）和光学相干断层扫描（OCT）。这种方法实现了目标跟踪和帧平均，并且已经描述了自动选择具有最小运动的参考帧的方法。然而，在参考帧中可能仍然存在不明显的运动伪影，并在注册、跟踪和平均的过程中传播。在这里，我们测试了一种以前提出的用于去除参考帧中运动伪影的方法，该方法利用了条带间互相关统计中的偏差。我们将该方法应用于具有模拟眼动伪影的合成视网膜图像以及受眼动影响的圆锥体镶嵌的真实 AO-SLO 图像和体积 AO-OCT 图像，在合成图像的情况下，该方法通过与图像的无运动版本进行直接比较得到验证。在真实的 AO 图像的情况下，通过比较未校正图像与校正图像的相关性、通过量化运动伪影对图像功率谱的影响以及通过对 AO-OCT B 扫描和共面投影的定性检查来验证性能。在所有情况下，所提出的方法都减少了运动伪影，并产生了更真实的视网膜图像。
