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Updated: Jun 18, 2026

Optic Nerve Sheath Point of Care Ultrasound: Image Acquisition
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Optic Nerve Sheath Point of Care Ultrasound: Image Acquisition

Published on: August 18, 2023

Practical considerations for optic nerve location in telemedicine.

T P Karnowski1, D Aykac, E Chaum

  • 1Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. karnowskitp@ornl.gov

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
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This study improves automated screening for diabetic retinopathy (DR) by enhancing optic nerve detection. Quality estimation boosts performance, enabling better telemedicine for early eye disease detection.

Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Rising global diabetes rates necessitate cost-effective screening for diabetic retinopathy (DR), a leading cause of vision impairment.
  • Telemedicine networks offer a scalable solution for widespread DR screening, integrating automated image analysis for efficiency.

Purpose of the Study:

  • To evaluate the impact of image quality estimation on an automated optic nerve (ON) detection algorithm.
  • To enhance the performance of DR screening using a fusion method combined with quality control.

Main Methods:

  • Developed and tested an optic nerve detection method with a confidence metric, incorporating quality estimation.
  • Validated the method on datasets from an ophthalmologist practice and large-scale telemedicine screening programs.

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  • Implemented a fusion approach combining automated detection with quality assessment.

    • Main Results:

    • Quality estimation significantly improved the optic nerve detection method's performance.
    • The fusion method demonstrated enhanced detection accuracy across varying image quality.
    • The system effectively identified images requiring physician review.

    Conclusions:

    • Automated quality estimation is crucial for reliable DR screening via telemedicine.
    • The fusion method enhances the robustness and accuracy of automated eye disease detection.
    • This approach supports a physician-in-the-loop system for complex cases, improving screening efficiency.