April 2014
Volume 55, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2014
Measurement of BMO-based optic disc area and rim area using Artificial Neural Network Principal component analysis (ANN-PCA) approach applied to 3D spectral domain optical coherence tomography optic nerve head images
Author Affiliations & Notes
  • Akram Belghith
    Hamilton Glaucoma Center, University of California San Diego, San Diego, CA
  • Christopher Bowd
    Hamilton Glaucoma Center, University of California San Diego, San Diego, CA
  • Felipe A Medeiros
    Hamilton Glaucoma Center, University of California San Diego, San Diego, CA
  • Robert N Weinreb
    Hamilton Glaucoma Center, University of California San Diego, San Diego, CA
  • Linda M Zangwill
    Hamilton Glaucoma Center, University of California San Diego, San Diego, CA
  • Footnotes
    Commercial Relationships Akram Belghith, None; Christopher Bowd, None; Felipe Medeiros, Allergan, Inc. (C), Carl Zeiss Meditec Inc. (R), Alcon Laboratories Inc (R), Alcon Laboratories Inc. (F), Allergan Inc (F), Allergan Inc. (R), Bausch & Lomb (F), Carl Zeiss Meditec Inc (F), Carl-Zeiss Meditec, Inc (C), Heidelberg Engineering, Inc (F), Merck Inc (F), National Eye Institute (F), Novartis (C), Reichert Inc (R), Reichert, Inc (F), Sensimed (F), Topcon, Inc (F); Robert Weinreb, Novartis (F), Aerie (F), Alcon (C), Allergan (C), Amkem (C), Bausch&Lomb (C), Carl Zeiss Meditec (F), Carl Zeiss Meditec, (C), EyeTechCare (C), Genentech (F), Heidelberg Engineering GmbH (F), National Eye Institute (F), Nidek (F), Optovue (F), Quark (C), Sensimed (C), Solx (C), Topcon (C), Topcon (F); Linda Zangwill, Carl Zeiss Meditec Inc (F), Heidelberg Engineering GmbH (F), Heidelberg Engineering GmbH (R), Optovue Inc (F), Topcon Medical Systems Inc (F)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 4766. doi:
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      Akram Belghith, Christopher Bowd, Felipe A Medeiros, Robert N Weinreb, Linda M Zangwill; Measurement of BMO-based optic disc area and rim area using Artificial Neural Network Principal component analysis (ANN-PCA) approach applied to 3D spectral domain optical coherence tomography optic nerve head images. Invest. Ophthalmol. Vis. Sci. 2014;55(13):4766.

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

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Abstract
 
Purpose
 

To propose a new approach for locating the Bruch's membrane opening (BMO) and estimating the BMO-based optic disc area and rim area of 3D Spectralis SD-OCT images (Heidelberg Engineering, 48 enhanced depth imaging EDI radial B-scans centered on the optic nerve head).

 
Methods
 

We formulated the detection of the BMO as a missing data problem where we jointly estimate the noise hyper-parameters and the segmented image. To deal with the overlapping of the Bruch's membrane and the retinal pigment epithelium layers due to the poor image resolution, we propose the use of an image deconvolution approach that consists of assigning to each layer a specific shape (or filter) and then estimating its hyper-parameters. To estimate the BMO-based optic disc size and rim area, we propose the use of a new regression method based on the Artificial Neural Network Principal component (ANN-PCA) analysis, which allows us to model irregularity in the BMO estimation due to scan shifts and/or poor image quality. Axial length corrected rim area measurements using this approach were compared to those from Cirrus SDOCT (Optic disc Cube 200x200, Cirrus OCT). The diagnostic accuracy of rim area, and rim to disc area ratio was also compared to Retinal Nerve Fiber Layer (RNFL) thickness measurements for glaucoma detection. Glaucoma diagnostic accuracy (area under receiver operating characteristic (AUROC)) was estimated using 105 glaucoma and 100 healthy eyes.

 
Results
 

The BMO-based disc area and rim area estimations with the new ANN-PCA approach using Spectralis EDI radial scans were similar to Cirrus measurements (Figure 1). The correlations between the two devices for the BMO-based disc area was R2 = 0.845 (p <0.001), for the rim area was R2 = 0.783 (p <0.001) and for the RNFL thickness was R2 = 0.848 (p <0.001). The diagnostic accuracy of RNFL tended to be better than rim area and rim to disc ratio but varied by instrument (Table 1).

 
Conclusions
 

Our proposed automated approach for estimating the BMO-based disc area and rim area measurements of 3D Spectralis SD-OCT images provides similar results to those from Cirrus SD-OCT. AUROC results suggest that RNFL may still be the measurement of choice for discriminating between glaucoma and healthy eyes.

     
Keywords: 549 image processing • 627 optic disc • 438 Bruch's membrane  
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