Opt Lett. 2020 Feb 1;45(3):694-697. doi: 10.1364/OL.383701.
Retinal optical coherence tomography (OCT) and OCT angiography (OCTA) suffer from the degeneration of image quality due to speckle noise and bulk-motion noise, respectively. Because the cross-sectional retina has distinct features in OCT and OCTA B-scans, existing digital filters that can denoise OCT efficiently are unable to handle the bulk-motion noise in OCTA. In this Letter, we propose a universal digital filtering approach that is capable of minimizing both types of noise. Considering that the retinal capillaries in OCTA are hard to differentiate in B-scans while having distinct curvilinear structures in 3D volumes, we decompose the volumetric OCT and OCTA data with 3D shearlets, thus efficiently separating the retinal tissue and vessels from the noise in this transform domain. Compared with wavelets and curvelets, the shearlets provide better representation of the layer edges in OCT and the vasculature in OCTA. Qualitative and quantitative results show the proposed method outperforms the state-of-the-art OCT and OCTA denoising methods. Also, the superiority of 3D denoising is demonstrated by comparing the 3D shearlet filtering with its 2D counterpart.
视网膜光学相干断层扫描（OCT）和 OCT 血管造影（OCTA）分别受到散斑噪声和体动噪声导致的图像质量下降的影响。由于 OCT 和 OCTA B 扫描中的横截面视网膜具有明显的特征，现有的可以有效去除 OCT 散斑噪声的数字滤波器无法处理 OCTA 中的体动噪声。在这封信件中，我们提出了一种通用的数字滤波方法，能够最小化这两种类型的噪声。考虑到 OCTA 中的毛细血管在 B 扫描中难以区分，而在 3D 体积中具有明显的弯曲结构，我们使用 3D 剪切波对 OCT 和 OCTA 体积数据进行分解，从而在这个变换域中有效地将视网膜组织和血管从噪声中分离出来。与小波和曲波相比，剪切波在 OCT 中的层边缘和 OCTA 中的脉管系统提供了更好的表示。定性和定量结果表明，所提出的方法优于最先进的 OCT 和 OCTA 去噪方法。此外，通过将 3D 剪切波滤波与 2D 对应物进行比较，还证明了 3D 去噪的优越性。
