April 2009
Volume 50, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2009
An In-painting Method for Combining Multiple SD-OCT Scans With Applications to Z-motion Recovery, Noise Reduction and Longitudinal Studies
Author Affiliations & Notes
  • D. A. Tolliver
    Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania
  • H. Ishikawa
    Sch Md/Eye Ctr, Ophth & Vis Sci Ctr/Eye & Ear Inst, Univ of Pittsburgh, Pittsburgh, Pennsylvania
    Bioengineering, Swanson School of Engineering, Univ. of Pittsburgh, Pittsburgh, Pennsylvania
  • J. S. Schuman
    Sch Md/Eye Ctr, Ophth & Vis Sci Ctr/Eye & Ear Inst, Univ of Pittsburgh, Pittsburgh, Pennsylvania
    Bioengineering, Swanson School of Engineering, Univ. of Pittsburgh, Pittsburgh, Pennsylvania
  • G. L. Miller
    Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania
  • Footnotes
    Commercial Relationships  D.A. Tolliver, None; H. Ishikawa, Bioptigen, P; J.S. Schuman, Bioptigen, P; Carl Zeiss Meditec, Inc., P; Alcon, R; Allergan, R; Carl Zeiss Meditec, Inc., R; Heidelberg Engineering, R; Merck, R; Lumenis, R; Optovue, R; Pfizer, R; G.L. Miller, None.
  • Footnotes
    Support  UPMC Grant, NSF Grant
Investigative Ophthalmology & Visual Science April 2009, Vol.50, 1100. doi:
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      D. A. Tolliver, H. Ishikawa, J. S. Schuman, G. L. Miller; An In-painting Method for Combining Multiple SD-OCT Scans With Applications to Z-motion Recovery, Noise Reduction and Longitudinal Studies. Invest. Ophthalmol. Vis. Sci. 2009;50(13):1100.

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

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Abstract

Purpose: : Eye motion during scan aquisition of SD-OCT volumes produces motion artifacts, and missing or poorly sampled regions, that ultimately hinder diagnosis and interfere with registration of multiple scans in longitudinal studies. We propose a method of combining multiple scans to produce a single rectified volume. The method can also be used to recover z-motion and remove in scans, as well as produce residual images and volumes for use in longitudinal analysis of disease progression.

Methods: : Single 3D SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec, Inc., Dublin, CA) scans and orthogonal raster 3D SD-OCT (Bioptigen SDOCT; Bioptigen, Inc., Research Triangle Park, NC) scan pairs were included in the study. Both scan types were used in computing the distributions over scleral and non-scleral shape. Given two scans, with orthogonal raster acquisition patterns, an optimization method motived by texture in-painting was used to select and stitch together a locally optimal collection of b-scan patches into a 3D volume. In the process, the relative z-motion of the eye in each scan is recovered. Figure 1 shows a transversal raster scan before and after rectification, the A-scan samples sites are linear in the left and automatically determined on the right.

Results: : Statistical shape models (based on PCA) were estimated of both scleral shape, over samples of annotated B-scans, and non-scleral shape over annotated transversal scans, derived from 3D-OCT scans of healthy subjects. The assessment measured the scleral shape along transversal images (across B-scans), see figure. In the perfect overlap area (figure, green box, a 63% area in scan pairs) 94.1% of the corrected transversal scans were more likely to have been sampled from the scleral shape distribution than the non-scleral shape distribution (at 98% confidence). 1.63 A-scans were used to estimate A-scan intensities in the combined volume, reducing visual noise.

Conclusions: : This automatic method produces a single combined scan with low residual z-motion and improved noise characteristics.

Keywords: image processing • imaging/image analysis: non-clinical • retina 
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