1. Axial Super-Resolution Study for Optical Coherence Tomography Images via Deep Learning

    Axial Super-Resolution Study for Optical Coherence Tomography Images via Deep Learning

    Optical coherence tomography (OCT) is a noninvasive, high resolution, and real-time imaging technology that has been used in ophthalmology and other medical fields. Limited by the point spread function of OCT system, it is difficult to optimize its spatial resolution only based on hardware. Digital image processing methods, especially deep learning, provide great potential in super-resolving images. In this paper, the matched axial low resolution (LR) and high resolution OCT image pairs from actual OCT imaging are collected to generate the dataset by our home-made spectral domain OCT (SD-OCT) system. Several methods are selected to super-resolve LR OCT images. It ...

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