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Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology.

Publication ,  Journal Article
Srinivasan, PP; Heflin, SJ; Izatt, JA; Arshavsky, VY; Farsiu, S
Published in: Biomed Opt Express
February 1, 2014

Accurate quantification of retinal layer thicknesses in mice as seen on optical coherence tomography (OCT) is crucial for the study of numerous ocular and neurological diseases. However, manual segmentation is time-consuming and subjective. Previous attempts to automate this process were limited to high-quality scans from mice with no missing layers or visible pathology. This paper presents an automatic approach for segmenting retinal layers in spectral domain OCT images using sparsity based denoising, support vector machines, graph theory, and dynamic programming (S-GTDP). Results show that this method accurately segments all present retinal layer boundaries, which can range from seven to ten, in wild-type and rhodopsin knockout mice as compared to manual segmentation and has a more accurate performance as compared to the commercial automated Diver segmentation software.

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Published In

Biomed Opt Express

DOI

ISSN

2156-7085

Publication Date

February 1, 2014

Volume

5

Issue

2

Start / End Page

348 / 365

Location

United States

Related Subject Headings

  • 5102 Atomic, molecular and optical physics
  • 4003 Biomedical engineering
  • 3212 Ophthalmology and optometry
  • 0912 Materials Engineering
  • 0205 Optical Physics
 

Citation

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Srinivasan, P. P., Heflin, S. J., Izatt, J. A., Arshavsky, V. Y., & Farsiu, S. (2014). Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology. Biomed Opt Express, 5(2), 348–365. https://doi.org/10.1364/BOE.5.000348
Srinivasan, Pratul P., Stephanie J. Heflin, Joseph A. Izatt, Vadim Y. Arshavsky, and Sina Farsiu. “Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology.Biomed Opt Express 5, no. 2 (February 1, 2014): 348–65. https://doi.org/10.1364/BOE.5.000348.
Srinivasan PP, Heflin SJ, Izatt JA, Arshavsky VY, Farsiu S. Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology. Biomed Opt Express. 2014 Feb 1;5(2):348–65.
Srinivasan, Pratul P., et al. “Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology.Biomed Opt Express, vol. 5, no. 2, Feb. 2014, pp. 348–65. Pubmed, doi:10.1364/BOE.5.000348.
Srinivasan PP, Heflin SJ, Izatt JA, Arshavsky VY, Farsiu S. Automatic segmentation of up to ten layer boundaries in SD-OCT images of the mouse retina with and without missing layers due to pathology. Biomed Opt Express. 2014 Feb 1;5(2):348–365.
Journal cover image

Published In

Biomed Opt Express

DOI

ISSN

2156-7085

Publication Date

February 1, 2014

Volume

5

Issue

2

Start / End Page

348 / 365

Location

United States

Related Subject Headings

  • 5102 Atomic, molecular and optical physics
  • 4003 Biomedical engineering
  • 3212 Ophthalmology and optometry
  • 0912 Materials Engineering
  • 0205 Optical Physics