June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
3D Motion Correction and Signal Improvement in High speed Polarization Sensitive Optical Coherence Tomography
Author Affiliations & Notes
  • Martin Kraus
    Pattern Recognition Lab and SAOT, University Erlangen Nuremberg, Erlangen, Germany
    Dept. of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology,, Cambridge, MA
  • Al-Hafeez Dhalla
    Dept. of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology,, Cambridge, MA
  • Jonathan Liu
    Dept. of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology,, Cambridge, MA
  • Kathrin Mohler
    Dept. of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology,, Cambridge, MA
  • Chen Lu
    Dept. of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology,, Cambridge, MA
  • Benjamin Potsaid
    Dept. of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology,, Cambridge, MA
  • Joachim Hornegger
    Pattern Recognition Lab and SAOT, University Erlangen Nuremberg, Erlangen, Germany
  • David Huang
    Casey Eye Institute, Oregon Health & Science University,, Portland, OR
  • James Fujimoto
    Dept. of Electrical Engineering and Computer Science and Research Laboratory of Electronics, Massachusetts Institute of Technology,, Cambridge, MA
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 5518. doi:
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      Martin Kraus, Al-Hafeez Dhalla, Jonathan Liu, Kathrin Mohler, Chen Lu, Benjamin Potsaid, Joachim Hornegger, David Huang, James Fujimoto; 3D Motion Correction and Signal Improvement in High speed Polarization Sensitive Optical Coherence Tomography. Invest. Ophthalmol. Vis. Sci. 2013;54(15):5518.

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

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Abstract

Purpose: Polarization sensitive Optical Coherence Tomography (PS-OCT) is a powerful technique to measure intrinsic optical properties of tissue such as birefringence in vivo and non-invasively. PS-OCT has been shown to be able to detect pathologic changes in the eye such as changes in the nerve fiber layer in glaucoma and can detect the RPE or the eye due to its depolarizing properties. In this work, we apply motion correction and merging techniques using orthogonal scan patterns to the field of PS-OCT data. The purpose of this work is to generate highly reliable, motion free 3D PS-OCT data sets in order to improve both signal quality and effective resolution of the PS-OCT information.

Methods: PS-OCT data was acquired using a high-speed swept source PS-OCT system based on single mode fiber with a polarization delay unit. The system provides four complex valued channels that contain the PS information. All these channels were generated in pre-processing as well as a total reflectivity or intensity channel. 3D registration and motion correction using orthogonal raster scan patterns was performed on the intensity channels. The resulting deformation fields were used to map the four other channels into the common motion corrected space. Further PS processing was performed after registration to obtain a merged retardation image.

Results: Experiments were performed on OCT volumes of healthy volunteers using multiple orthogonal volumes of the optic nerve and macula regions. Visual inspection shows that the technique is able to register and motion correct and intensity channels and map the PS-OCT channels into a common space. Compared to a single input volume both the intensity and retardation images show no motion artifacts and increased SNR.

Conclusions: We believe that 3D imaging with high speed PS-OCT systems in combination with motion correction and merging of multiple registered volumes has the potential to play an important role in improving the diagnostic power of PS-OCT.

Keywords: 549 image processing • 602 motion-3D • 552 imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound)  
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