Department of Electrical Engineering, University of Wisconsin-Milwaukee, WI 53211, USA.
Department of Computer Science, University of Wisconsin-Milwaukee, WI 53211, USA.
Med Image Anal. 2017 Apr;37:129-145. doi: 10.1016/j.media.2017.02.002. Epub 2017 Feb 4.
In this paper, we review state-of-the-art techniques to correct eye motion artifacts in Optical Coherence Tomography (OCT) imaging. The methods for eye motion artifact reduction can be categorized into two major classes: (1) hardware-based techniques and (2) software-based techniques. In the first class, additional hardware is mounted onto the OCT scanner to gather information about the eye motion patterns during OCT data acquisition. This information is later processed and applied to the OCT data for creating an anatomically correct representation of the retina, either in an offline or online manner. In software based techniques, the motion patterns are approximated either by comparing the acquired data to a reference image, or by considering some prior assumptions about the nature of the eye motion. Careful investigations done on the most common methods in the field provides invaluable insight regarding future directions of the research in this area. The challenge in hardware-based techniques lies in the implementation aspects of particular devices. However, the results of these techniques are superior to those obtained from software-based techniques because they are capable of capturing secondary data related to eye motion during OCT acquisition. Software-based techniques on the other hand, achieve moderate success and their performance is highly dependent on the quality of the OCT data in terms of the amount of motion artifacts contained in them. However, they are still relevant to the field since they are the sole class of techniques with the ability to be applied to legacy data acquired using systems that do not have extra hardware to track eye motion.
在本文中,我们回顾了校正光学相干断层扫描(OCT)成像中眼动伪影的最新技术。用于减少眼动伪影的方法可分为两大类:(1)基于硬件的技术和(2)基于软件的技术。在第一类中,将额外的硬件安装到 OCT 扫描仪上,以获取 OCT 数据采集过程中眼动模式的信息。然后,以离线或在线方式处理此信息并将其应用于 OCT 数据,以创建视网膜的解剖学正确表示。在基于软件的技术中,通过将获取的数据与参考图像进行比较,或者通过考虑关于眼动性质的某些先验假设,来近似运动模式。对该领域最常见方法进行的仔细研究为该领域的未来研究方向提供了宝贵的见解。基于硬件的技术的挑战在于特定设备的实现方面。但是,这些技术的结果优于基于软件的技术的结果,因为它们能够捕获 OCT 采集过程中与眼动相关的辅助数据。另一方面,基于软件的技术取得了中等程度的成功,并且其性能高度依赖于 OCT 数据的质量,具体取决于其中包含的运动伪影的数量。但是,它们仍然与该领域相关,因为它们是唯一一类能够应用于使用没有跟踪眼动的额外硬件的系统获取的旧数据的技术。