A statistical model of retinal optical coherence tomography image data

Prathamesh Kulkarni, Diana Lozano, George Zouridakis, Michael Twa

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

2 Scopus citations

Abstract

Optical coherence tomography (OCT) is an important mode of biomedical imaging for the diagnosis and management of ocular disease. Here we report on the construction of a synthetic retinal OCT image data set that may be used for quantitative analysis of image processing methods. Synthetic image data were generated from statistical characteristics of real images (n 14). Features include: multiple stratified layers with representative thickness, boundary gradients, contour, and intensity distributions derived from real data. The synthetic data also include retinal vasculature with typical signal obscuration beneath vessels. This synthetic retinal image can provide a realistic simulated data set to help quantify the performance of image processing algorithms.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages6127-6130
Number of pages4
DOIs
StatePublished - 2011
Externally publishedYes
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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