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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 2, Iss. 6 — Jun. 1, 2011
  • pp: 1524–1538

Robust automatic segmentation of corneal layer boundaries in SDOCT images using graph theory and dynamic programming

Francesco LaRocca, Stephanie J. Chiu, Ryan P. McNabb, Anthony N. Kuo, Joseph A. Izatt, and Sina Farsiu  »View Author Affiliations

Biomedical Optics Express, Vol. 2, Issue 6, pp. 1524-1538 (2011)

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Segmentation of anatomical structures in corneal images is crucial for the diagnosis and study of anterior segment diseases. However, manual segmentation is a time-consuming and subjective process. This paper presents an automatic approach for segmenting corneal layer boundaries in Spectral Domain Optical Coherence Tomography images using graph theory and dynamic programming. Our approach is robust to the low-SNR and different artifact types that can appear in clinical corneal images. We show that our method segments three corneal layer boundaries in normal adult eyes more accurately compared to an expert grader than a second grader—even in the presence of significant imaging outliers.

© 2011 OSA

OCIS Codes
(100.0100) Image processing : Image processing
(100.2960) Image processing : Image analysis
(110.4500) Imaging systems : Optical coherence tomography
(170.4470) Medical optics and biotechnology : Ophthalmology

ToC Category:
Image Processing

Original Manuscript: March 8, 2011
Revised Manuscript: May 6, 2011
Manuscript Accepted: May 10, 2011
Published: May 12, 2011

Francesco LaRocca, Stephanie J. Chiu, Ryan P. McNabb, Anthony N. Kuo, Joseph A. Izatt, and Sina Farsiu, "Robust automatic segmentation of corneal layer boundaries in SDOCT images using graph theory and dynamic programming," Biomed. Opt. Express 2, 1524-1538 (2011)

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