University of Washington, Department of Bioengineering, Seattle, Washington, United States.
University of Washington, Department of Bioengineering, Seattle, Washington, United StatesbUniversity of Washington, Department of Ophthalmology, Seattle, Washington, United States.
J Biomed Opt. 2017 Jun 1;22(6):66013. doi: 10.1117/1.JBO.22.6.066013.
When using optical coherence tomography angiography (OCTA), the development of artifacts due to involuntary movements can severely compromise the visualization and subsequent quantitation of tissue microvasculatures. To correct such an occurrence, we propose a motion compensation method to eliminate artifacts from human skin OCTA by means of step-by-step rigid affine registration, rigid subpixel registration, and nonrigid B-spline registration. To accommodate this remedial process, OCTA is conducted using two matching all-depth volume scans. Affine transformation is first performed on the large vessels of the deep reticular dermis, and then the resulting affine parameters are applied to all-depth vasculatures with a further subpixel registration to refine the alignment between superficial smaller vessels. Finally, the coregistration of both volumes is carried out to result in the final artifact-free composite image via an algorithm based upon cubic B-spline free-form deformation. We demonstrate that the proposed method can provide a considerable improvement to the final en face OCTA images with substantial artifact removal. In addition, the correlation coefficients and peak signal-to-noise ratios of the corrected images are evaluated and compared with those of the original images, further validating the effectiveness of the proposed method. We expect that the proposed method can be useful in improving qualitative and quantitative assessment of the OCTA images of scanned tissue beds.
当使用光学相干断层扫描血管造影术（OCTA）时，由于非自愿运动而产生的伪影会严重影响组织微血管的可视化和后续定量分析。为了纠正这种情况，我们提出了一种运动补偿方法，通过逐步刚性仿射配准、刚性亚像素配准和非刚性 B 样条配准来消除人体皮肤 OCTA 中的伪影。为了适应这种矫正过程，使用两个匹配的全深度体积扫描进行 OCTA。首先对深层网状真皮的大血管进行仿射变换，然后将得到的仿射参数应用于全深度血管，进一步进行亚像素配准，以细化浅层较小血管的对齐。最后，通过基于三次 B 样条自由变形的算法对两个体积进行配准，得到最终无伪影的复合图像。我们证明，所提出的方法可以显著提高最终的 OCTA 图像的质量，并去除大量伪影。此外，还评估和比较了校正后图像的相关系数和峰值信噪比与原始图像的相关系数和峰值信噪比，进一步验证了所提出方法的有效性。我们期望所提出的方法可以用于改善对扫描组织床的 OCTA 图像的定性和定量评估。
