Automated retinal layer segmentation and characterization

Jonathan Luisi, David Briley, Adam Boretsky, Massoud Motamedi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Spectral Domain Optical Coherence Tomography (SD-OCT) is a valuable diagnostic tool in both clinical and research settings. The depth-resolved intensity profiles generated by light backscattered from discrete layers of the retina provide a non-invasive method of investigating progressive diseases and injury within the eye. This study demonstrates the application of steerable convolution filters capable of automatically separating gradient orientations to identify edges and delineate tissue boundaries. The edge maps were recombined to measure thickness of individual retinal layers. This technique was successfully applied to longitudinally monitor changes in retinal morphology in a mouse model of laser-induced choroidal neovascularization (CNV) and human data from age-related macular degeneration patients. The steerable filters allow for direct segmentation of noisy images, while novel recombination of weaker segmentations allow for denoising post-segmentation. The segmentation before denoising strategy allows the rapid detection of thin retinal layers even under suboptimal imaging conditions..

Original languageEnglish (US)
Title of host publicationTranslational Biophotonics
PublisherSPIE
ISBN (Print)9780819496263
DOIs
StatePublished - Jan 1 2014
EventTranslational Biophotonics - Houston, TX, United States
Duration: May 19 2014May 20 2014

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9155
ISSN (Print)1605-7422

Other

OtherTranslational Biophotonics
CountryUnited States
CityHouston, TX
Period5/19/145/20/14

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Luisi, J., Briley, D., Boretsky, A., & Motamedi, M. (2014). Automated retinal layer segmentation and characterization. In Translational Biophotonics [91551N] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9155). SPIE. https://doi.org/10.1117/12.2057814