April 2011
Volume 52, Issue 14
Free
ARVO Annual Meeting Abstract  |   April 2011
Segmentation-Based Registration of Retinal Optical Coherence Tomography Images with Pathology
Author Affiliations & Notes
  • Xinyu Song
    Biomedical Engineering,
    Duke University, Durham, North Carolina
  • Rolando Estrada
    Computer Science,
    Duke University, Durham, North Carolina
  • Stephanie J. Chiu
    Biomedical Engineering,
    Duke University, Durham, North Carolina
  • Al-Hafeez Dhalla
    Biomedical Engineering,
    Duke University, Durham, North Carolina
  • Cynthia A. Toth
    Ophthalmology & Biomedical Engineering,
    Duke University, Durham, North Carolina
  • Joseph A. Izatt
    Biomedical Engineering & Ophthalmology,
    Duke University, Durham, North Carolina
  • Sina Farsiu
    Ophthalmology & Biomedical Engineering,
    Duke University, Durham, North Carolina
  • Footnotes
    Commercial Relationships  Xinyu Song, None; Rolando Estrada, None; Stephanie J. Chiu, Bioptigen (P); Al-Hafeez Dhalla, None; Cynthia A. Toth, Alcon, Bioptigen (P), Alcon, Bioptigen, Genentech, Sirion (F); Joseph A. Izatt, Bioptigen (I, C, P); Sina Farsiu, Bioptigen (P), Genentech (F)
  • Footnotes
    Support  This project was funded in part by the American Health Assistance Foundation (M2010008) and Research to Prevent Blindness unrestricted funds.
Investigative Ophthalmology & Visual Science April 2011, Vol.52, 1309. doi:
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      Xinyu Song, Rolando Estrada, Stephanie J. Chiu, Al-Hafeez Dhalla, Cynthia A. Toth, Joseph A. Izatt, Sina Farsiu; Segmentation-Based Registration of Retinal Optical Coherence Tomography Images with Pathology. Invest. Ophthalmol. Vis. Sci. 2011;52(14):1309.

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

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Abstract

Purpose: : Accurate construction of 3D retinal volumes from SDOCT is hindered by the presence of patient eye motion. Additionally, common volume acquisition protocols result in low azimuthal resolution along the direction of successive B-scans. To improve the accuracy of quantitative volumetric measurements, e.g. drusen volume, it is desirable to attain isotropic lateral resolution by capturing and fusing the information of 2 volume scans at 0- and 90- degree orientations. Unfortunately, the fundamental assumption that registered frames are inherently similar limits application of most classic image registration techniques for this task. We have previously developed algorithms for reliable segmentation of up to 8 intra-retinal boundaries. In this project, we utilize the segmentation information to aid in reconstructing SDOCT volumes free of motion artifacts.

Methods: : We captured 2 perpendicularly oriented SDOCT volumes with 100 B-scans (1000 A-scans each) from a 6.6mm square retinal area of five subjects with non-neovascular AMD. Many of the B-scans included relatively large drusen. We used our software to segment the retinal layers. To register consecutive B-scans, we minimized the rate of change in location of these layers along the azimuthal direction. Moreover, we adjusted the position of B-scans in each volume by enforcing a retinal anatomy condition estimated by segmenting the corresponding layers in the perpendicularly oriented volume. To register the two perpendicularly oriented SDOCT volumes, we detected and matched the vessels on their axially projected summed-voxel-projections. As a quantitative measure of registration reliability, we defined the rate of the nerve fiber layer (NFL) position change (RNPC) as the absolute value difference between the pixel position of the NFL in one frame and the average position of the NFL in the before and after frames.

Results: : Visual examination of the registered 3D volumes attested to the accuracy of the proposed technique. The RNPC mean and standard deviation at 0- and 90- degree volumes were 3.0 ± 1.2 and 2.9 ± 1.1 pixels for non-registered frames and 1.8 ± 0.7, 1.7 ± 0.5 pixels for registered frames, respectively.

Conclusions: : We achieved reliable registration of volumetric B-scan data through segmentation of B-scans in combination with a small number of B-scans acquired in the orthogonal direction.

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