Multi-Scale Reconstruction of Undersampled Spectral-Spatial OCT Data for Coronary Imaging Using Deep Learning.
Multi-Scale Reconstruction of Undersampled Spectral-Spatial OCT Data for Coronary Imaging Using Deep Learning.
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DOI：
10.1109/tbme.2022.3175670
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发表时间：
2022-12
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冠状动脉疾病（CAD）是一种高发病率和死亡率的心血管疾病。血管内光学相干断层扫描（IVOCT）被认为是诊断和治疗冠心病的最佳成像系统。受奈奎斯特定理的约束，IVOCT中的密集采样达到高分辨率以描绘细胞结构/特征。冠状动脉成像的高空间分辨率和快速扫描速率之间存在权衡。在本文中，我们提出了一个可行的频谱空间采集方法，缩小采样过程中的频谱和空间域，同时保持高质量的图像重建。缩减时间表提高了数据采集速度，而无需任何硬件修改。此外，我们提出了一个统一的多尺度重建框架，即多尺度光谱空间放大网络（MSSMN），以解决高度缩小（压缩）OCT图像与灵活的放大因子。我们将所提出的方法纳入光谱域OCT（SD-OCT）成像的临床特征，如支架和钙化病变的人体冠状动脉样本。我们的实验结果表明，频谱空间缩小的数据可以更好地重建比数据，是缩小单独在频谱或空间域。此外，我们观察到更好的重建性能，使用MSSMN比使用现有的重建方法。我们的采集方法和多尺度重建框架相结合，可以在冠状动脉介入治疗期间实现更快的高分辨率SD-OCT检查。
Coronary artery disease (CAD) is a cardiovascular condition with high morbidity and mortality. Intravascular optical coherence tomography (IVOCT) has been considered as an optimal imagining system for the diagnosis and treatment of CAD. Constrained by Nyquist theorem, dense sampling in IVOCT attains high resolving power to delineate cellular structures/features. There is a trade-off between high spatial resolution and fast scanning rate for coronary imaging. In this paper, we propose a viable spectral-spatial acquisition method that down-scales the sampling process in both spectral and spatial domain while maintaining high quality in image reconstruction. The down-scaling schedule boosts data acquisition speed without any hardware modifications. Additionally, we propose a unified multi-scale reconstruction framework, namely MultiscaleSpectral-Spatial-Magnification Network (MSSMN), to resolve highly down-scaled (compressed) OCT images with flexible magnification factors. We incorporate the proposed methods into Spectral Domain OCT (SD-OCT) imaging of human coronary samples with clinical features such as stent and calcified lesions. Our experimental results demonstrate that spectral-spatial down-scaled data can be better reconstructed than data that is down-scaled solely in either spectral or spatial domain. Moreover, we observe better reconstruction performance using MSSMN than using existing reconstruction methods. Our acquisition method and multi-scale reconstruction framework, in combination, may allow faster SD-OCT inspection with high resolution during coronary intervention.