论文标题
OCT-GAN：人类视神经头的光学相干断层扫描图像的单步影片和噪声去除
OCT-GAN: Single Step Shadow and Noise Removal from Optical Coherence Tomography Images of the Human Optic Nerve Head
论文作者
论文摘要
OCT B扫描中的斑点噪声和视网膜阴影阻塞了重要的边缘，细质地和深层组织，可防止算法和临床医生的准确和强大的诊断。我们开发了一个单一的过程，该过程成功地从10.4ms的单一框架B扫描中成功删除了噪声和视网膜阴影。所提出算法的平均平均梯度幅度（AGM）比当前的最新算法高出57.2％，而平均峰信号与噪声比（PSNR），与噪声比（CNR）的对比（CNR），结构相似性指数（SSIM）分别增加了11.1％，154％，154％和187％与单型唯一b-Scans相比。视网膜神经纤维层（RNFL），光感受器层（PR）和视网膜色素上皮（RPE）层的平均内部对比度（ILC）改善从0.362 \ pm 0.133降低至0.142 0.0590 \ pm 0.0451。提出的算法减少了长图像获取时间的必要性，最大程度地减少了昂贵的硬件要求，并减少了OCT图像中的运动伪像。
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 \pm 0.133 to 0.142 \pm 0.102, 0.449 \pm 0.116 to 0.0904 \pm 0.0769, 0.381 \pm 0.100 to 0.0590 \pm 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.
