Abstract

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.

© 2022 Optica Publishing Group

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