Quantitative 3D-OCT motion correction with tilt and illumination correction, robust similarity measure and regularization.
Quantitative 3D-OCT motion correction with tilt and illumination correction, robust similarity measure and regularization.
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DOI：
10.1364/boe.5.002591
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发表时间：
2014-08-01
影响因子：
3.4
通讯作者：
Hornegger J
中科院分区：
文献类型：
--
作者：
Kraus MF;Liu JJ;Schottenhamml J;Chen CL;Budai A;Branchini L;Ko T;Ishikawa H;Wollstein G;Schuman J;Duker JS;Fujimoto JG;Hornegger J
照明、信号质量、倾斜和运动量的变化对基于后处理的3D-OCT运动校正算法提出了挑战。我们提出了一种先进的3D-OCT运动校正算法，使用图像配准和正交光栅扫描模式，旨在解决这些挑战。引入了一种基于伪Huber范数的强度相似性度量和一种基于伪L0.5范数的正则化方案。制定了两阶段登记办法。在第一阶段中，仅粗略校正轴向运动和轴向倾斜。然后将该结果用作第二阶段完全优化的起点。在预处理中，采用基于偏置场估计的方法来校正输入体积中的照明差异。使用SD-OCT系统从73只健康和青光眼眼睛采集的大量数据进行定量评价。使用每个位置的三个独立正交体积对采集的视神经乳头和黄斑区的OCT体积来评估再现性。先进的运动校正算法，使用本文提出的技术进行了比较，一个基本的算法对应于一个较早的版本，并执行没有运动校正。基于分割的措施，如层位置，视网膜和神经纤维厚度，以及血管图案的错误进行了评估。定量结果一致表明，通过使用先进的算法，再现性得到了显着改善，这也显着优于基本算法。所有数据的平均绝对视网膜厚度差的平均值为9.9 μ m（无运动校正）、7.1 μ m（使用基本算法）和5.0 μ m（使用高级算法）。类似地，对于基本算法，血管似然图误差减小到未校正误差的69%，对于高级算法，减小到未校正误差的47%。这些结果表明，我们先进的运动校正算法有可能大大提高来自3D-OCT数据的定量测量的可靠性。
Variability in illumination, signal quality, tilt and the amount of motion pose challenges for post-processing based 3D-OCT motion correction algorithms. We present an advanced 3D-OCT motion correction algorithm using image registration and orthogonal raster scan patterns aimed at addressing these challenges. An intensity similarity measure using the pseudo Huber norm and a regularization scheme based on a pseudo L0.5 norm are introduced. A two-stage registration approach was developed. In the first stage, only axial motion and axial tilt are coarsely corrected. This result is then used as the starting point for a second stage full optimization. In preprocessing, a bias field estimation based approach to correct illumination differences in the input volumes is employed. Quantitative evaluation was performed using a large set of data acquired from 73 healthy and glaucomatous eyes using SD-OCT systems. OCT volumes of both the optic nerve head and the macula region acquired with three independent orthogonal volume pairs for each location were used to assess reproducibility. The advanced motion correction algorithm using the techniques presented in this paper was compared to a basic algorithm corresponding to an earlier version and to performing no motion correction. Errors in segmentation-based measures such as layer positions, retinal and nerve fiber thickness, as well as the blood vessel pattern were evaluated. The quantitative results consistently show that reproducibility is improved considerably by using the advanced algorithm, which also significantly outperforms the basic algorithm. The mean of the mean absolute retinal thickness difference over all data was 9.9 um without motion correction, 7.1 um using the basic algorithm and 5.0 um using the advanced algorithm. Similarly, the blood vessel likelihood map error is reduced to 69% of the uncorrected error for the basic and to 47% of the uncorrected error for the advanced algorithm. These results demonstrate that our advanced motion correction algorithm has the potential to improve the reliability of quantitative measurements derived from 3D-OCT data substantially.