Opt Lett. 2022 Sep 1;47(17):4544-4547. doi: 10.1364/OL.464501.
A large amount of lateral noise will be generated in blood flow imaging with optical coherence tomography angiography (OCTA) due to the presence of muscle shaking, heartbeat, and respiration, resulting in the deterioration of images. In this paper, to the best of our knowledge, for the first time, the spatial frequency information of motion noise in the blood flow signal region is used to remove the motion noise and false connections in the blood flow signal region. The effectiveness of the proposed adaptive denoising algorithm is verified by the imaging of finger blood flow. It is found that OCTA with different projection methods has improved signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) after applying our algorithm. It is also found that the visual effect of the original blood flow image based on standard deviation projection is better, but mean projection is the most sensitive to the algorithm, and the average SNR and CNR are improved by 5.7 dB and 8.9 dB, respectively.
由于肌肉抖动、心跳和呼吸的存在，光相干断层扫描血管造影 (OCTA) 的血流成象会产生大量的侧向噪声，从而导致图像质量恶化。在本文中，据我们所知，首次利用血流信号区域运动噪声的空间频率信息来去除血流信号区域中的运动噪声和虚假连接。通过对指血流成像的验证，证明了所提出的自适应去噪算法的有效性。结果发现，应用我们的算法后，不同投影方法的 OCTA 的信噪比 (SNR) 和对比噪声比 (CNR) 都得到了提高。还发现，基于标准差投影的原始血流图像的视觉效果更好，但均值投影对算法最敏感，平均 SNR 和 CNR 分别提高了 5.7dB 和 8.9dB。
