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Proceedings Paper

Enhancing resolution and contrast in second-harmonic generation microscopy using an advanced maximum likelihood estimation restoration method
Author(s): Mayandi Sivaguru; Mohammad M. Kabir; Manas Ranjan Gartia; David S. C. Biggs; Barghav S. Sivaguru; Vignesh A. Sivaguru; Zachary T. Berent; Amy J. Wagoner Johnson; Glenn A. Fried; Gang Logan Liu; Sakthivel Sadayappan; Kimani C. Toussaint
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Paper Abstract

Second-harmonic generation (SHG) microscopy is a label-free imaging technique to study collagenous materials in extracellular matrix environment with high resolution and contrast. However, like many other microscopy techniques, the actual spatial resolution achievable by SHG microscopy is reduced by out-of-focus blur and optical aberrations that degrade particularly the amplitude of the detectable higher spatial frequencies. Being a two-photon scattering process, it is challenging to define a point spread function (PSF) for the SHG imaging modality. As a result, in comparison with other two-photon imaging systems like two-photon fluorescence, it is difficult to apply any PSF-engineering techniques to enhance the experimental spatial resolution closer to the diffraction limit. Here, we present a method to improve the spatial resolution in SHG microscopy using an advanced maximum likelihood estimation (AdvMLE) algorithm to recover the otherwise degraded higher spatial frequencies in an SHG image. Through adaptation and iteration, the AdvMLE algorithm calculates an improved PSF for an SHG image and enhances the spatial resolution by decreasing the full-width-at-halfmaximum (FWHM) by ~20%. Similar results are consistently observed for biological tissues with varying SHG sources, such as gold nanoparticles and collagen in porcine feet tendons. By obtaining an experimental transverse spatial resolution of ~400 nm, we show that the AdvMLE algorithm brings the practical spatial resolution closer to the theoretical diffraction limit. Our approach is suitable for adaptation in micro-nano CT and MRI imaging, which has the potential to impact diagnosis and treatment of human diseases.

Paper Details

Date Published: 21 February 2017
PDF: 8 pages
Proc. SPIE 10069, Multiphoton Microscopy in the Biomedical Sciences XVII, 1006908 (21 February 2017); doi: 10.1117/12.2256534
Show Author Affiliations
Mayandi Sivaguru, Univ. of Illinois at Urbana-Champaign (United States)
Mohammad M. Kabir, Univ. of Illinois at Urbana-Champaign (United States)
Manas Ranjan Gartia, Louisiana State Univ. (United States)
David S. C. Biggs, KB Imaging Solutions LLC (United States)
Barghav S. Sivaguru, Univ. of Illinois at Urbana-Champaign (United States)
Vignesh A. Sivaguru, Univ. of Illinois at Urbana-Champaign (United States)
Zachary T. Berent, Univ. of Illinois at Urbana-Champaign (United States)
Amy J. Wagoner Johnson, Univ. of Illinois at Urbana-Champaign (United States)
Glenn A. Fried, Univ. of Illinois at Urbana-Champaign (United States)
Gang Logan Liu, Univ. of Illinois at Urbana-Champaign (United States)
Sakthivel Sadayappan, Univ. of Cincinnati College of Medicine (United States)
Kimani C. Toussaint, Univ. of Illinois at Urbana-Champaign (United States)


Published in SPIE Proceedings Vol. 10069:
Multiphoton Microscopy in the Biomedical Sciences XVII
Ammasi Periasamy; Peter T. C. So; Karsten König; Xiaoliang S. Xie, Editor(s)

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