July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Automated geographic atrophy detection in OCT volumes
Author Affiliations & Notes
  • Qi Yang
    Research and Development, Topcon Healthcare Solutions, Oakland, New Jersey, United States
  • Ying Dong
    Research and Development, Topcon Healthcare Solutions, Oakland, New Jersey, United States
  • Kanichi Tokuda
    Research and Development, Topcon Corporation, Tokyo, Japan
  • Taiki Aimi
    Research and Development, Topcon Corporation, Tokyo, Japan
  • Masahiro Akiba
    Research and Development, Topcon Corporation, Tokyo, Japan
  • José Maria Ruiz-Moreno
    Department of Ophthalmology, Castilla La Mancha University, Ciudad Real, Spain
  • Charles Reisman
    Research and Development, Topcon Healthcare Solutions, Oakland, New Jersey, United States
  • Footnotes
    Commercial Relationships   Qi Yang, Topcon Healthcare Solutions (E); Ying Dong, Topcon Healthcare Solutions (E); Kanichi Tokuda, Topcon Corporation (E); Taiki Aimi, Topcon Corporation (E); Masahiro Akiba, Topcon Corporation (E); José Maria Ruiz-Moreno, None; Charles Reisman, Topcon Healthcare Solutions (E)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 3225. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Qi Yang, Ying Dong, Kanichi Tokuda, Taiki Aimi, Masahiro Akiba, José Maria Ruiz-Moreno, Charles Reisman; Automated geographic atrophy detection in OCT volumes. Invest. Ophthalmol. Vis. Sci. 2018;59(9):3225.

      Download citation file:


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

      ×
  • Supplements
Abstract

Purpose : To present an automated geographic atrophy (GA) detection algorithm for quantifying GA area as seen on swept source optical coherence tomography (OCT) scans of patients with either uni-focal or multi-focal GA.

Methods : The detection algorithm is based on integrated attenuation, in which the signal intensities of the RPE complex are normalized by the chorioscleral signal as part of the calculation [1]. A series of image processing steps, including preprocessing, auto-thresholding and region growing, are applied to the 2D integrated attenuation map generated from a 3D volume for a result of binary GA region map. A post-processing procedure follows to refine the GA region. To test the accuracy, the manually delineated GA regions in corresponding fundus auto fluorescence (FAF) images were compared to the automatic detection results of volumes acquired from macular and wide 3D scans from a one-micron wavelength swept-source device (DRI OCT Triton, Topcon Corp., Tokyo, Japan). To test the repeatability, multiple 3D scans of the same GA eye were detected and intra-class correlation coefficients and the mean of standard deviations were calculated.

Results : The currently developed GA detection method demonstrated the ability to reliably delineate GA with good repeatability. The GA areas that were automatically detected in OCT were found to be correlated to the GA area that was manually delineated in FAF.

Conclusions : The proposed automated GA detection method was able to produce reliable results and is promising towards practical clinical usage in GA area quantification and progression tracking.
Reference[1]: Yang, Q. and Reisman, C. United States patent US9,526,412.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×