Speckle noise and retinal shadows within OCT B-scans occlude important edges, fine textures and deep tissues, preventing accurate and robust diagnosis by algorithms and clinicians. We developed a single process that successfully removed both noise and retinal shadows from unseen single-frame B-scans within 10.4ms. Mean average gradient magnitude (AGM) for the proposed algorithm was 57.2% higher than current state-of-the-art, while mean peak signal to noise ratio (PSNR), contrast to noise ratio (CNR), and structural similarity index metric (SSIM) increased by 11.1%, 154% and 187% respectively compared to single-frame B-scans. Mean intralayer contrast (ILC) improvement for the retinal nerve fiber layer (RNFL), photoreceptor layer (PR) and retinal pigment epithelium (RPE) layers decreased from 0.362 ± 0.133 to 0.142 ± 0.102, 0.449 ± 0.116 to 0.0904 ± 0.0769, 0.381 ± 0.100 to 0.0590 ± 0.0451 respectively. The proposed algorithm reduces the necessity for long image acquisition times, minimizes expensive hardware requirements and reduces motion artifacts in OCT images.

中文翻译：

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OCT-GAN：从人类视神经头的光学相干断层扫描图像中去除一步阴影和噪声

OCT B扫描中的斑点噪声和视网膜阴影会遮挡重要的边缘，精细的纹理和深层组织，从而阻止算法和临床医生进行准确而可靠的诊断。我们开发了一个单一过程，成功地在10.4毫秒内从看不见的单帧B扫描中消除了噪声和视网膜阴影。提出的算法的平均平均梯度幅度（AGM）比当前的最新技术高57.2％，而平均峰值信噪比（PSNR），对比噪声比（CNR）和结构相似性指标度量（与单帧B扫描相比，SSIM分别增加了11.1％，154％和187％。视网膜神经纤维层（RNFL），感光层（PR）和视网膜色素上皮层（RPE）的平均层内对比度（ILC）改善从0.362±0.133降至0.142±0.102、0.449±0.116降至0。0904±0.0769、0.381±0.100至0.0590±0.0451。所提出的算法减少了长图像获取时间的必要性，最大程度地降低了昂贵的硬件要求，并减少了OCT图像中的运动伪像。