2019/05/31 by Jonathan H. Mason, Mike E. Davies, Pierre Bagnaninchi +1 · 8 citations
Biochemistry, Genetics and Molecular Biology · Engineering · Physics and Astronomy · #Advanced Fluorescence Microscopy Techniques #Algorithm #Artificial intelligence #Coherence (philosophical gambling strategy) #Computer science #Computer vision #Fourier transform #Interferometry #Iterative reconstruction #Microscopy #Optical Coherence Tomography Applications #Optical coherence tomography #Optics #Photoacoustic and Ultrasonic Imaging #Physics #Regularization (linguistics) #Synthetic aperture radar #eess.IV #physics.med-ph #physics.optics
paper · pdf · open access · doi:10.1364/oe.379216
published in Optics Express 28(3), 3879 (Optica Publishing Group) · 17 pages, 7 figures. The images have been compressed for arxiv - please follow DOI for full resolution
openalex publication_date 2019/12/14 · arxiv created 2020/01/31 · arxiv updated 2020/02/03 · openalex created_date 2020/11/23 · openalex updated_date 2026/08/05
We present a computational method for full-range interferometric synthetic aperture microscopy (ISAM) under dispersion encoding. With this, one can effectively double the depth range of optical coherence tomography (OCT), whilst dramatically enhancing the spatial resolution away from the focal plane. To this end, we propose a model-based iterative reconstruction (MBIR) method, where ISAM is directly considered in an optimization approach, and we make the discovery that sparsity promoting regularization effectively recovers the full-range signal. Within this work, we adopt an optimal nonuniform discrete fast Fourier transform (NUFFT) implementation of ISAM, which is both fast and numerically stable throughout iterations. We validate our method with several complex samples, scanned with a commercial SD-OCT system with no hardware modification. With this, we both demonstrate full-range ISAM imaging and significantly outperform combinations of existing methods.