June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
High-contrast and polarization-artifact-free optical coherence tomography by maximum a-posteriori intensity estimation
Author Affiliations & Notes
  • Aaron C Chan
    Computational Optics Group, University of Tsukuba, Tsukuba, Ibaraki, Japan
  • Young-Joo Hong
    Computational Optics Group, University of Tsukuba, Tsukuba, Ibaraki, Japan
  • Shuichi Makita
    Computational Optics Group, University of Tsukuba, Tsukuba, Ibaraki, Japan
  • Masahiro Miura
    Department of Ophthalmology, Tokyo Medical University Ibaraki Medical Center, Ami, Ibaraki, Japan
  • Yoshiaki Yasuno
    Computational Optics Group, University of Tsukuba, Tsukuba, Ibaraki, Japan
  • Footnotes
    Commercial Relationships   Aaron Chan, Nidek (F), Tomey Corporation (F), Topcon Corporation (F); Young-Joo Hong, Nidek (F), Tomey Corporation (F), Topcon Corporation (F); Shuichi Makita, Nidek (F), Tomey Corporation (F), Topcon Corporation (F); Masahiro Miura, Alcon (F), Allergan (F), Bayer (F), Novartis (F), Santen (F); Yoshiaki Yasuno, Nidek (F), Tomey Corporation (F), Topcon Corporation (F)
  • Footnotes
    Support  JSPS KAKENHI15K13371; MEXT Program for Building Innovation Ecosystem
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 5437. doi:
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    • Get Citation

      Aaron C Chan, Young-Joo Hong, Shuichi Makita, Masahiro Miura, Yoshiaki Yasuno; High-contrast and polarization-artifact-free optical coherence tomography by maximum a-posteriori intensity estimation. Invest. Ophthalmol. Vis. Sci. 2017;58(8):5437.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : OCT images of birefringence tissue may suffer polarization artifacts. Polarization-diversity detection OCT (PD-OCT) can suppress the artifacts, but it then suffers from low signal-to-noise ratio (SNR) and signal offset at low signal regions. To address this, we combine maximum a-posteriori (MAP) intensity estimation with PD-OCT. It improves SNR, reduces signal-offset and removes polarization artifacts.

Methods : 6-mm transverse-range images of the right maculae and ONH of 5 subjects without marked eye disease were scanned by a custom-built 1-µm Jones matrix OCT at 100,000 A-lines/s. The axial resolution is 6.2 µm in tissue. Each tomogram consists of 4 images: 2 probe × 2 detection polarizations. The four images are complex averaged with phase correction to create an image equivalent of standard OCT. Also, images from the same detection polarization are complex averaged after phase correction. The resulting two images are equivalent to those obtained by PD detection. Four repeated B-scans of standard OCT (S) or PD signals were combined by MAP estimation algorithm or intensity averaging (A). The two combined PD signals are then summed to generate a PD-OCT image. These are denoted as S-MAP, S-A, PD-MAP, and PD-A. The MAP algorithm computes the most likely estimation of true OCT intensity from multiple measured intensities. It also improves the SNR and reduces the signal offset. Attenuation coefficients were also computed from the intensities.

Results : Fig. 1 shows S-MAP and S-A images of a macula. It can be seen that S-MAP (b) has lower signal-offset in the vitreous and better SNR than S-A (a). It is also evident in the corresponding histograms (c, d). The corresponding S-MAP attenuation image (f, h) shows better differentiation of attenuation levels than S-A (e, g).
Fig. 2 shows S-MAP (a) and PD-MAP images (b) of another macula. Polarization artifacts appear in the sclera (a, red arrow) as alternating high and low-intensity bands. These are suppressed in (b). These artifacts are typically seen in birefringent tissues such as peripapillary sclera (c, red arrow, another subject), which are suppressed in PD-OCT (d).

Conclusions : The combination of PD detection and MAP estimation enables polarization artifact free imaging while preserving high-SNR and low signal-offset. This is useful for imaging deep birefringent tissue, such as sclera and lamina cribrosa.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

 

 

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