1. N2NSR‐OCT: Simultaneous denoising and super‐resolution in optical coherence tomography images using semi‐supervised deep learning

    N2NSR‐OCT: Simultaneous denoising and super‐resolution in optical coherence tomography images using semi‐supervised deep learning

    Optical coherence tomography (OCT) imaging shows a significant potential in clinical routines due to its noninvasive property. However, the quality of OCT images is generally limited by inherent speckle noise of OCT imaging and low sampling rate. To obtain high signal‐to‐noise ratio (SNR) and high‐resolution (HR) OCT images within a short scanning time, we presented a learning‐based method to recover high‐quality OCT images from noisy and low‐resolution OCT images. We proposed a semi‐supervised learning approach named N2NSR‐OCT, to generate denoised and super‐resolved OCT images simultaneously using up‐ and down‐sampling networks ...

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