Axial super-resolution for optical coherence tomography with the iterative adaptive approach

Jos de Wit; Kostas Angelopoulos; Jeroen Kalkman; George-Othon Glentis

doi:10.1364/DH.2021.DF4F.3

OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
OSA Technical Digest (Optica Publishing Group, 2021),
paper DF4F.3
•https://doi.org/10.1364/DH.2021.DF4F.3

Axial super-resolution for optical coherence tomography with the iterative adaptive approach

Jos de Wit, Kostas Angelopoulos, Jeroen Kalkman, and George-Othon Glentis

Digital Holography and Three-Dimensional Imaging 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-89-7

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Novel Diagnostic and Data Analysis (DF4F)

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J. de Wit, K. Angelopoulos, J. Kalkman, and G. Glentis, "Axial super-resolution for optical coherence tomography with the iterative adaptive approach," in OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), H. Hua, B. Javidi, M. Martinez-Corral, O. Matoba, A. Stern, S. Thibault, T. Alieva, J. Ke, F. Willomitzer, F. Okten, P. Silveira, P. Banerjee, E. Stoykova, D. Chu, J. Park, F. Imai, C. Joo, M. Digman, D. Gardner, S. Gladysz, D. LeMaster, S. Basu, and O. Korotkova, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper DF4F.3.

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Abstract

Spectral estimation can improve axial resolution for optical coherence tomography reconstruction. Using a computationally-efficient implementation of the non-parametric iterative adaptive approach, we significantly improve the axial resolution over Fourier-based reconstruction and obtain high-quality B-scans in processing times below 2 seconds.

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