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Related Experiment Video

Updated: Jun 14, 2026

Doppler Optical Coherence Tomography of Retinal Circulation
10:46

Doppler Optical Coherence Tomography of Retinal Circulation

Published on: September 18, 2012

A computer algorithm to quantitatively assess quality of digital optic disc images.

Michele Moscaritolo1, Henry Jampel, Ingrid Zimmer-Galler

  • 1Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.

Ophthalmic Surgery, Lasers & Imaging : the Official Journal of the International Society for Imaging in the Eye
|March 24, 2010
PubMed
Summary

A new computerized algorithm accurately assesses optic disc photograph quality for glaucoma management. This tool reliably identifies unreadable images, aiding in clinical review and research consistency.

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Computer Science

Background:

  • Optic disc photography is crucial for glaucoma diagnosis and monitoring.
  • Accurate image quality assessment is essential for reliable glaucoma management.
  • Current quality assessment relies on subjective human review.

Purpose of the Study:

  • To develop and validate an objective, computerized algorithm for assessing optic disc photograph quality.
  • To mimic the quality assessment procedures of human observers.
  • To evaluate the algorithm's performance on both film-based and digital images.

Main Methods:

  • A computerized algorithm was developed to objectively assess image quality.
  • The algorithm was tested on film-based (mydriatic) and digital (non-mydriatic) optic disc images.

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Last Updated: Jun 14, 2026

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Using Retinal Imaging to Study Dementia
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  • Image sharpness was evaluated by masked human readers, and algorithm performance was analyzed using receiver operating characteristic (ROC) curves.

    • Main Results:

    • The algorithm achieved an area under the ROC curve of 1.0 for identifying unreadable images in both digital and film-based datasets.
    • For differentiating unreadable from mediocre images, the algorithm achieved AUCs of 0.91 (digital) and 1.0 (film-based).
    • The algorithm successfully identified all unreadable images in the pilot study.

    Conclusions:

    • The developed algorithm demonstrates high accuracy in identifying unreadable optic disc images.
    • This objective quality assessment tool shows potential for improving glaucoma management workflows.
    • Further research is needed to assess the algorithm's generalizability across different imaging devices and fundus locations.