September 2016
Volume 57, Issue 12
Open Access
ARVO Annual Meeting Abstract  |   September 2016
Automated Retinal Segmentation for Widefield OCT, with applications to OCT Angiography
Author Affiliations & Notes
  • Giovanni Gregori
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida, United States
  • Philip J Rosenfeld
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida, United States
  • Luiz Roisman
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida, United States
  • Karen B Schaal
    Ophthalmology, Bascom Palmer Eye Institute, Miami, Florida, United States
  • Footnotes
    Commercial Relationships   Giovanni Gregori, Carl Zeiss Meditec (F), Carl Zeiss Meditec (P); Philip Rosenfeld, Carl Zeiss Meditec (F), Carl Zeiss Meditec (R); Luiz Roisman, None; Karen Schaal, None
  • Footnotes
    Support  Research support from Carl Zeiss Meditec. NIH Center Core Grant P30EY014801, DOD Grant# W81XWH-13-1-0048, Research to Prevent Blindness Unrestricted Grant, NIH Grant EY021834
Investigative Ophthalmology & Visual Science September 2016, Vol.57, 446. doi:
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    • Get Citation

      Giovanni Gregori, Philip J Rosenfeld, Luiz Roisman, Karen B Schaal; Automated Retinal Segmentation for Widefield OCT, with applications to OCT Angiography. Invest. Ophthalmol. Vis. Sci. 2016;57(12):446.

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

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Abstract

Purpose : The goal was to produce a new fast, robust algorithm capable of segmenting retinal layers from OCT images. The algorithm is intended for use on the very large datasets and field of views acquired using a widefield Swept Source OCT prototype in clinical situations, for the study of eyes with significant pathologies. This is particularly important for applications in OCT angiographic imaging where visualization of blood flow within the appropriate anatomical regions is crucial for the appropriate clinical interpretation of images.

Methods : A new fully automated algorithm was used to segment several retinal layers from both OCT intensity and OCT angiography datasets. In particular, we studied images obtained from a prototype 100-kHz SS-OCT instrument (Carl Zeiss Meditec, Dublin, CA) with a central wavelength of 1,050 nm. This instrument is capable of acquiring both intensity and angiography scans over retinal areas up to 12x12mm (512x512 to 1000x1000 cubes for intensity scans, 450x450 cubes for OCT angiography).

Results : The segmentation algorithm generated slabs used for OCT angiography en face visualization. We obtained Inner Retinal (ILM to OPL), Outer Retinal (OPL to RPE, OPL to BM, RPE to BM), Choriocapillaris, and Choroidal slabs. Expert comparison with OCT angiography images obtained with a supervised semi-automated segmentation showed equivalent results. Total processing time was below 30s in a Matlab environment on a Dell Precision laptop.

Conclusions : The algorithm produced a robust, fast segmentation on datasets from patients with a wide variety of retinal pathologies. It is shown to be useful for generating widefield OCT angiography slabs in a typical clinical setting.

This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.

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