Significance: Full-field optical angiography is critical for vascular disease research and clinical diagnosis. Existing methods struggle to improve the temporal and spatial resolutions simultaneously.
Aim: Spatiotemporal absorption fluctuation imaging (ST-AFI) is proposed to achieve dynamic blood flow imaging with high spatial and temporal resolutions.
Approach: ST-AFI is a dynamic optical angiography based on a low-coherence imaging system and U-Net. The system was used to acquire a series of dynamic red blood cell (RBC) signals and static background tissue signals, and U-Net is used to predict optical absorption properties and spatiotemporal fluctuation information. U-Net was generally used in two-dimensional blood flow segmentation as an image processing algorithm for biomedical imaging. In the proposed approach, the network simultaneously analyzes the spatial absorption coefficient differences and the temporal dynamic absorption fluctuation.
Results: The spatial resolution of ST-AFI is up to 4.33 μm, and the temporal resolution is up to 0.032 s. In vivo experiments on 2.5-day-old chicken embryos were conducted. The results demonstrate that intermittent RBCs flow in capillaries can be resolved, and the blood vessels without blood flow can be suppressed.
Conclusions: Using ST-AFI to achieve convolutional neural network (CNN)-based dynamic angiography is a novel approach that may be useful for several clinical applications. Owing to their strong feature extraction ability, CNNs exhibit the potential to be expanded to other blood flow imaging methods for the prediction of the spatiotemporal optical properties with improved temporal and spatial resolutions.
Keywords: U-Net; dynamic blood flow imaging; optical angiography; spatiotemporal absorption fluctuation imaging.