1. Resolution enhancement in low transverse sampling optical coherence tomography angiography using deep learning

    Resolution enhancement in low transverse sampling optical coherence tomography angiography using deep learning

    Optical coherence tomography angiography (OCTA) requires high transverse sampling rates for visualizing retinal and choroidal capillaries, which impedes the popularization of the OCTA technique due to the high cost of speedy acquisition systems. On the other hand, current wide-field OCTA using low transverse sampling causes the underestimation of vascular biomarkers in quantitative analysis. In this paper, we propose to use deep learning to repair the resolution degeneration induced by the low transverse sampling. We conducted preliminary experiments on converting the centrally cropped 3 × 3 mm2 field of view (FOV) of the 8 × 8 mm2 foveal OCTA images (a sampling rate ...

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