Registration of retinal sequences from new video-ophthalmoscopic camera.
Registration of retinal sequences from new video-ophthalmoscopic camera.
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DOI：
10.1186/s12938-016-0191-0
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发表时间：
2016-05-20
影响因子：
3.9
通讯作者：
Liberdova I
中科院分区：
文献类型：
--
作者：
Kolar R;Tornow RP;Odstrcilik J;Liberdova I
分析视网膜的快速时间变化已经成为诊断视频眼科的重要组成部分。它可以研究视网膜组织中的血液动力学过程，如血压变化引起的血管内径变化，颅内-眼内压差影响的自发性静脉搏动，视网膜组织光反射变化导致的血容量变化，以及使用激光散斑对比成像的血流。对于这种应用，必须执行记录序列的图像配准。在这里，我们使用一种新的非散瞳视频检眼镜来简单快速地获取低信噪比的视网膜序列。我们介绍了一种新颖的两步快速图像配准方法。第一阶段的相位相关去除了较大的眼球运动。第二阶段的卢卡斯-卡纳德跟踪去除了小的眼球运动。我们提出了稳健的自适应的跟踪点选择，这是基于跟踪的方法中最重要的部分。我们还描述了一种基于维管束树强度轮廓的配准结果的定量评估方法。在23个序列(5840帧)上评估获得的配准误差为视盘内0.78±0.67像素，视盘外1.39±0.63像素。我们将结果与常用的基于Lucas-Kanade跟踪和尺度不变特征变换的方法进行了比较，后者的结果较差。该方法可以有效地纠正视网膜序列中的特定移位和旋转帧。每一帧的配准结果(X和Y方向的移动以及眼睛的旋转)也可以用于在单点注视任务期间的眼动评估。
Analysis of fast temporal changes on retinas has become an important part of diagnostic video-ophthalmology. It enables investigation of the hemodynamic processes in retinal tissue, e.g. blood-vessel diameter changes as a result of blood-pressure variation, spontaneous venous pulsation influenced by intracranial-intraocular pressure difference, blood-volume changes as a result of changes in light reflection from retinal tissue, and blood flow using laser speckle contrast imaging. For such applications, image registration of the recorded sequence must be performed. Here we use a new non-mydriatic video-ophthalmoscope for simple and fast acquisition of low SNR retinal sequences. We introduce a novel, two-step approach for fast image registration. The phase correlation in the first stage removes large eye movements. Lucas-Kanade tracking in the second stage removes small eye movements. We propose robust adaptive selection of the tracking points, which is the most important part of tracking-based approaches. We also describe a method for quantitative evaluation of the registration results, based on vascular tree intensity profiles. The achieved registration error evaluated on 23 sequences (5840 frames) is 0.78 ± 0.67 pixels inside the optic disc and 1.39 ± 0.63 pixels outside the optic disc. We compared the results with the commonly used approaches based on Lucas-Kanade tracking and scale-invariant feature transform, which achieved worse results. The proposed method can efficiently correct particular frames of retinal sequences for shift and rotation. The registration results for each frame (shift in X and Y direction and eye rotation) can also be used for eye-movement evaluation during single-spot fixation tasks.