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Segmentation of the Surfaces of the Retinal Layer from OCT Images

  • Mona Haeker
  • Michael Abràmoff
  • Randy Kardon
  • Milan Sonka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)

Abstract

We have developed a method for the automated segmentation of the internal limiting membrane and the pigment epithelium in 3-D OCT retinal images. Each surface was found as a minimum s-t cut from a geometric graph constructed from edge/regional information and a priori-determined surface constraints. Our approach was tested on 18 3-D data sets (9 from patients with normal optic discs and 9 from patients with papilledema) obtained using a Stratus OCT-3 scanner. Qualitative analysis of surface detection correctness indicates that our method consistently found the correct surfaces and outperformed the proprietary algorithm used in the Stratus OCT-3 scanner. For example, for the internal limiting membrane, 4% of the 2-D scans had minor failures with no major failures using our approach, but 19% of the 2-D scans using the Stratus OCT-3 scanner had minor or complete failures.

Keywords

Optical Coherence Tomography Retinal Thickness Retinal Layer Optical Coherence Tomography Image Geometric Graph 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mona Haeker
    • 1
    • 2
  • Michael Abràmoff
    • 1
    • 3
  • Randy Kardon
    • 3
  • Milan Sonka
    • 1
    • 3
  1. 1.Department of Electrical and Computer EngineeringThe University of IowaIowa CityUSA
  2. 2.Department of Biomedical EngineeringThe University of IowaIowa CityUSA
  3. 3.Department of Ophthalmology and Visual SciencesThe University of IowaIowa CityUSA

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