April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Increased OCT Nerve Fiber Layer Thickness Measurement Reproducibility With Image Registration Based Motion Correction
Author Affiliations & Notes
  • Martin Kraus
    Pattern Recognition Lab, University Erlangen Nuremberg, Erlangen, Germany
    Research Laboratory of Electronics and Dept of EECS, Massachusetts Inst of Technology, Cambridge, Massachusetts
  • Lauren Branchini
    New England Eye Center, Boston, Massachusetts
  • Tony H. Ko
    Optovue Inc., Fremont, California
  • Richard A. Bilonick
    Department of Ophthalmology, UPMC Eye Center, Pittsburgh, Pennsylvania
  • Yuanmu Deng
    Optovue Inc., Fremont, California
  • Jay S. Duker
    New England Eye Center, Boston, Massachusetts
  • Joel S. Schuman
    Department of Ophthalmology, UPMC Eye Center, Pittsburgh, Pennsylvania
  • Joachim Hornegger
    Pattern Recognition Lab, University Erlangen Nuremberg, Erlangen, Germany
    Graduate School in Advanced Optical Technologies (SAOT), Erlangen, Germany
  • James G. Fujimoto
    Research Laboratory of Electronics and Dept of EECS, Massachusetts Inst of Technology, Cambridge, Massachusetts
  • Footnotes
    Commercial Relationships  Martin Kraus, None; Lauren Branchini, None; Tony H. Ko, Optovue Inc. (E); Richard A. Bilonick, None; Yuanmu Deng, Optovue Inc. (E); Jay S. Duker, Carl Zeiss Meditech, Inc. (F), Topcon Medical Systems, Inc. (F); Joel S. Schuman, Bioptigen, Inc. (P), Carl Zeiss Meditec, Inc. (P); Joachim Hornegger, None; James G. Fujimoto, Carl Zeiss Meditec, Inc. (P), Optovue, Inc. (I)
  • Footnotes
    Support  NIH R01-EY011289-24, R01-EY013178-10, R01-EY019029-02, R01-EY013516-07, AFOSR FA9550-07-1-0101
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 1335. doi:
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    • Get Citation

      Martin Kraus, Lauren Branchini, Tony H. Ko, Richard A. Bilonick, Yuanmu Deng, Jay S. Duker, Joel S. Schuman, Joachim Hornegger, James G. Fujimoto; Increased OCT Nerve Fiber Layer Thickness Measurement Reproducibility With Image Registration Based Motion Correction. Invest. Ophthalmol. Vis. Sci. 2011;52(14):1335.

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

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Abstract

Purpose: : OCT imaging enables quantitative morphometry of Nerve Fiber Layer thickness for diagnosis and tracking progression in glaucoma. Motion artifacts and signal quality limit the reproducibility of these measurements. We apply a new motion correction algorithm that uses 2 3D-OCT data sets acquired with orthogonal raster scan patterns. A pilot study on normal subjects was conducted to evaluate if this can improve the reproducibility of NFL-thickness measurements.

Methods: : Correction was performed by acquiring two 3D-OCT data sets with orthogonal raster scan patterns. An image registration based method was implemented to estimate motion in each data set. The corrected data sets were merged to create a single motion free data set with improved SNR. n=13 healthy subjects were scanned using a commercial spectral domain OCT system (Optovue RTVue). Volumes consisting of 200 by 200 A-Scans over 6 by 6 mm centered on the ONH were imaged. A standard raster scan data set was acquired along with a motion corrected data set and the acquisition was repeated 3 times. Mean NFL-thicknesses of 3.45 mm diameter virtual circumpapillary scans of original and registered volumes were measured, using a varying number of segments. Reproducibility was assessed by calculating bias and imprecision using a structural equation model. Segmentation and ONH-centering were performed using software provided by Optovue.

Results: : The registered volumes showed correction of transverse and axial eye motion and also increased SNR and reduced speckle. Global mean RNFL thickness measurement showed estimated imprecision of 2.03 um for registered vs. 3.31 um in the original volumes. For 4 segments the mean imprecision was 2.62 um vs. 4.43 um.

Conclusions: : The motion correction method yields reduced motion artifacts and improved SNR. RNFL measurements in normal subjects show improved reproducibility. These preliminary results suggest that the developed motion correction algorithm can play a significant role in improving reproducibility of NFL thickness measurements by reducing effects from eye motion and improving image quality.

Keywords: image processing • imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • nerve fiber layer 
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