Abstract
In this paper, we present an automated algorithm framework for determining the optimal parameters for interferometric synthetic aperture microscopy (ISAM). Three stages of ISAM reconstruction, including dispersion correction, spectral domain resampling and computational adaptive optics (CAO) aberration correction are automated. This algorithm framework significantly lowers the background requirement for operating and calibrating ISAM machines, while achieving fast, near-optimal ISAM reconstruction on optical coherence tomography (OCT) datasets.
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