背景:在光学相干断层扫描血管造影(OCTA)的临床应用中,重复扫描和平均方法可以提供更好的对比度,并减少最终结果中的斑点噪声,这对于高精度地可视化和量化血管成分是有用的,再现性,和可靠性。然而,不可避免的患者运动对这种方法提出了挑战。这项研究的目的是通过引入3D配准方法来配准光学相干断层扫描(OCT)/OCTA扫描,以对多个扫描进行精确的体积平均,从而改善信噪比(SNR)并提高量化精度,从而应对这一挑战。
方法:所提出的方法利用了刚性仿射变换和非刚性B样条变换,其中通过OCT结构图像上的平均随机梯度下降来优化和计算它们的参数。此外,我们还引入了多级分辨率方法,以进一步提高我们提出的方法的鲁棒性和计算速度。在人体皮肤和眼睛的体内成像上测试了成像性能,并通过SNR进行了评估。峰值信噪比(PSNR)和归一化相关系数(NCC)。
结果:本研究招募了5名受试者以获得皮肤和视网膜的体内图像。所提出的配准和平均方法在血管连通性和信噪比方面提供了成像性能的实质性改进。平均中重复体积数的增加改善了所有评估的指标,即,SNR,PSNR和NCC。在10次重复的体积平均之后,实现了SNR从10到40dB的改善。
结论:所提出的3D配准和平均方法在减少斑点噪声和抑制运动伪影方面是有效的,从而提高SNR,最终平均图像的PSNR和NCC度量。预计所提出的算法将在更好的可视化和更可靠的体内OCT和OCTA数据的量化方面实用。这将有利于OCT的临床应用。
BACKGROUND: In the clinical applications of optical coherence tomography angiography (OCTA), the repeated scanning and averaging method can provide better contrast with reduced speckle noises in the final results, which are useful for visualizing and quantifying vascular components with high accuracy, reproducibility, and reliability. However, the inevitable patient motion presents a challenge to this method. The objective of this study is to meet this challenge by introducing a 3D registration method to register optical coherence tomography (OCT)/OCTA scans for precise volume averaging of multiple scans to improve the signal-to-noise ratio (SNR) and increase quantification accuracy.
METHODS: The proposed method utilized both rigid affine transformation and non-rigid B-spline transformation in which their parameters were optimized and calculated by the average stochastic gradient descent on OCT structural images. In addition, we also introduced a multi-level resolution approach to further improve the robustness and computational speed of our proposed method. The imaging performance was tested on in vivo imaging of human skin and eye and assessed by SNR, peak signal-to-noise ratio (PSNR) and normalized correlation coefficient (NCC).
RESULTS: Five subjects were enrolled in this study for obtaining in vivo images of skin and retina. The proposed registration and averaging method provided substantial improvements of the imaging performance in terms of vessel connectivity and signal to noise ratio. The increase of repeated volume numbers in the averaging improves all the metrics assessed, i.e., SNR, PSNR and NCC. An improvement of the SNR from 10 to 40 dB after 10 repeated volumetric averaging was achieved.
CONCLUSIONS: The proposed 3D registration and averaging method is effective in reducing speckle noises and suppressing motion artifacts, thereby improving SNR, PSNR and NCC metrics for final averaged images. It is expected that the proposed algorithm would be practically useful in better visualization and more reliable quantification of in vivo OCT and OCTA data, which would be beneficial to OCT clinical applications.