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Sub2Full:在无干净数据的情况下分割光谱以增强光学相干断层扫描去斑效果

Sub2Full: split spectrum to boost optical coherence tomography despeckling without clean data.

作者信息

Wang Lingyun, Sahel Jose A, Pi Shaohua

出版信息

Opt Lett. 2024 Jun 1;49(11):3062-3065. doi: 10.1364/OL.518906.

Abstract

Optical coherence tomography (OCT) suffers from speckle noise, causing the deterioration of image quality, especially in high-resolution modalities such as visible light OCT (vis-OCT). Here, we proposed an innovative self-supervised strategy called Sub2Full (S2F) for OCT despeckling without clean data. This approach works by acquiring two repeated B-scans, splitting the spectrum of the first repeat as a low-resolution input, and utilizing the full spectrum of the second repeat as the high-resolution target. The proposed method was validated on vis-OCT retinal images visualizing sublaminar structures in the outer retina and demonstrated superior performance over state-of-the-art Noise2Noise (N2N) and Noise2Void (N2V) schemes.

摘要

光学相干断层扫描(OCT)存在散斑噪声问题,会导致图像质量下降,尤其是在可见光OCT(vis-OCT)等高分辨率模式下。在此,我们提出了一种名为Sub2Full(S2F)的创新型自监督策略,用于在没有干净数据的情况下对OCT进行去噪。该方法通过获取两次重复的B扫描来工作,将第一次重复扫描的光谱作为低分辨率输入进行分割,并将第二次重复扫描的全光谱用作高分辨率目标。所提出的方法在vis-OCT视网膜图像上进行了验证,这些图像可显示外视网膜中的层下结构,并证明其性能优于现有技术的噪声到噪声(N2N)和噪声到空白(N2V)方案。

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