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Proceedings Paper

Volumetric optical coherence microscopy enabled by aberrated optics (Conference Presentation)
Author(s): Jeffrey A. Mulligan; Siyang Liu; Steven G. Adie

Paper Abstract

Optical coherence microscopy (OCM) is an interferometric imaging technique that enables high resolution, non-invasive imaging of 3D cell cultures and biological tissues. Volumetric imaging with OCM suffers a trade-off between high transverse resolution and poor depth-of-field resulting from defocus, optical aberrations, and reduced signal collection away from the focal plane. While defocus and aberrations can be compensated with computational methods such as interferometric synthetic aperture microscopy (ISAM) or computational adaptive optics (CAO), reduced signal collection must be physically addressed through optical hardware. Axial scanning of the focus is one approach, but comes at the cost of longer acquisition times, larger datasets, and greater image reconstruction times. Given the capabilities of CAO to compensate for general phase aberrations, we present an alternative method to address the signal collection problem without axial scanning by using intentionally aberrated optical hardware. We demonstrate the use of an astigmatic spectral domain (SD-)OCM imaging system to enable single-acquisition volumetric OCM in 3D cell culture over an extended depth range, compared to a non-aberrated SD-OCM system. The transverse resolution of the non-aberrated and astigmatic imaging systems after application of CAO were 2 um and 2.2 um, respectively. The depth-range of effective signal collection about the nominal focal plane was increased from 100 um in the non-aberrated system to over 300 um in the astigmatic system, extending the range over which useful data may be acquired in a single OCM dataset. We anticipate that this method will enable high-throughput cellular-resolution imaging of dynamic biological systems over extended volumes.

Paper Details

Date Published: 24 April 2017
PDF: 1 pages
Proc. SPIE 10076, High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management II, 1007617 (24 April 2017); doi: 10.1117/12.2253437
Show Author Affiliations
Jeffrey A. Mulligan, Cornell Univ. (United States)
Siyang Liu, Cornell Univ. (United States)
Steven G. Adie, Cornell Univ. (United States)


Published in SPIE Proceedings Vol. 10076:
High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management II
Kevin K. Tsia; Keisuke Goda, Editor(s)

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