Local quality assessment for optical coherence tomography

Peter Barnum, Mei Chen, Hiroshi Ishikawa, Gadi Wollstein, Joel Schuman

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

Abstract

Optical Coherence Tomography (OCT) is a non-invasive tool for visualizing the retina. It is increasingly used to diagnose eye diseases such as glaucoma and diabetic maculopathy. However, diagnosis is only possible when the layers of the retina can be easily distinguished, which is when the images are evenly illuminated. Automated OCT quality assessment (i.e. signal strength) is only available for images as a whole. In this work, we present an automated method for local quality assessment. For training data, three OCT experts label the quality of each individual a-scan line in 270 OCT images. We extract features that are insensitive to pathology, and employ a hierarchy of support vector machines and histogram-based metrics. Our trained classifier is able to determine not only when signal strength is low, but also when it will affect doctors' diagnostic ability. Our results improve over the state of the art in OCT quality assessment.

Original languageEnglish (US)
Title of host publication2008 5th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, Proceedings, ISBI
Pages392-395
Number of pages4
DOIs
StatePublished - 2008
Event2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI - Paris, France
Duration: May 14 2008May 17 2008

Publication series

Name2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

Other

Other2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI
Country/TerritoryFrance
CityParis
Period5/14/085/17/08

Keywords

  • Image quality assessment
  • Optical coherence tomography

ASJC Scopus subject areas

  • Biomedical Engineering

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