Automation of interferometric synthetic aperture microscopy

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.

[1]  J. Duker,et al.  Ultrahigh-resolution, high-speed, Fourier domain optical coherence tomography and methods for dispersion compensation. , 2004, Optics express.

[2]  Adeel Ahmad,et al.  Computational adaptive optics for broadband optical interferometric tomography of biological tissue , 2012, Proceedings of the National Academy of Sciences.

[3]  Nathan D. Shemonski,et al.  Computed optical interferometric tomography for high-speed volumetric cellular imaging. , 2014, Biomedical optics express.

[4]  Stephen A. Boppart,et al.  Interferometric Synthetic Aperture Microscopy , 2007, OFC/NFOEC 2008 - 2008 Conference on Optical Fiber Communication/National Fiber Optic Engineers Conference.

[5]  Stephen A. Boppart,et al.  Real-time in vivo computed optical interferometric tomography , 2013, Nature Photonics.