视网膜疾病早期检测的探索：基于3D CycleGAN的光学相干断层扫描到共聚焦显微镜的转换
The Quest for Early Detection of Retinal Disease: 3D CycleGAN-based Translation of Optical Coherence Tomography into Confocal Microscopy
AI总结：
提出基于3D CycleGAN的无监督框架，将体内OCT转换为体外共聚焦显微镜图像，首次利用3D信息，引入OCT2Confocal数据集，实现高保真转换，优于现有方法。
摘要：
光学相干断层扫描（OCT）和共聚焦显微镜在视网膜成像中至关重要，各自具有独特的优势和局限性。体内OCT提供快速、非侵入性成像，但可能存在清晰度问题和运动伪影，而体外共聚焦显微镜提供高分辨率、细胞细节丰富的彩色图像，但具有侵入性并引发伦理问题。为了融合两种模态的优势，我们提出了一种基于无监督3D CycleGAN的新型框架，用于将未配对的体内OCT图像转换为体外共聚焦显微镜图像。这是首次尝试利用OCT固有的3D信息并将其转换为共聚焦显微镜丰富、详细的彩色域。我们还引入了一个独特的数据集OCT2Confocal，包含小鼠OCT和共聚焦视网膜图像，为跨模态图像转换研究的发展提供了便利，并建立了基准。我们的模型在定量和定性上均进行了评估，实现了Fréchet初始距离（FID）分数0.766和核初始距离（KID）分数低至0.153，并获得了领先的主观平均意见分数（MOS）。我们的模型在有限数据下表现出优于现有方法的图像保真度和质量。我们的方法有效地从3D共聚焦图像中合成颜色信息，紧密接近目标结果，并提示在眼科诊断和监测应用中具有增强的潜力。
英文摘要：
Optical coherence tomography (OCT) and confocal microscopy are pivotal in retinal imaging, offering distinct advantages and limitations. In vivo OCT offers rapid, non-invasive imaging but can suffer from clarity issues and motion artifacts, while ex vivo confocal microscopy, providing high-resolution, cellular-detailed color images, is invasive and raises ethical concerns. To bridge the benefits of both modalities, we propose a novel framework based on unsupervised 3D CycleGAN for translating unpaired in vivo OCT to ex vivo confocal microscopy images. This marks the first attempt to exploit the inherent 3D information of OCT and translate it into the rich, detailed color domain of confocal microscopy. We also introduce a unique dataset, OCT2Confocal, comprising mouse OCT and confocal retinal images, facilitating the development of and establishing a benchmark for cross-modal image translation research. Our model has been evaluated both quantitatively and qualitatively, achieving Fréchet Inception Distance (FID) scores of 0.766 and Kernel Inception Distance (KID) scores as low as 0.153, and leading subjective Mean Opinion Scores (MOS). Our model demonstrated superior image fidelity and quality with limited data over existing methods. Our approach effectively synthesizes color information from 3D confocal images, closely approximating target outcomes and suggesting enhanced potential for diagnostic and monitoring applications in ophthalmology.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
