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Related Experiment Video

Updated: Dec 30, 2025

Optic Nerve Sheath Point of Care Ultrasound: Image Acquisition
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Automated Optic Nerve Sheath Diameter Measurement Using Super-pixel Analysis.

Reza Soroushmehr, Krishna Rajajee, Craig Williamson

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 18, 2020
    PubMed
    Summary

    This study introduces an automated image processing method to measure optic nerve sheath diameter, offering a faster and more accurate alternative to manual measurements for predicting increased intracranial pressure (ICP). The automated approach shows comparable accuracy to expert manual measurements.

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    Area of Science:

    • Neuroscience
    • Medical Imaging
    • Biomedical Engineering

    Background:

    • The optic nerve, surrounded by cerebrospinal fluid, can exhibit sheath diameter changes correlating with intracranial pressure (ICP).
    • Ultrasound imaging offers a non-invasive method for measuring optic nerve sheath diameter (ONSD).
    • Manual ONSD measurement is time-consuming and prone to human error, limiting its clinical utility.

    Purpose of the Study:

    • To develop and validate an automated image processing technique for measuring optic nerve sheath diameter.
    • To assess the accuracy and efficiency of the automated method compared to manual measurements.

    Main Methods:

    • Image denoising
    • Region of interest detection using a line integral method
    • Super-pixel analysis for diameter measurement

    Main Results:

    • The proposed automated method demonstrated comparable accuracy to manual measurements by two expert clinicians.
    • The average percentage error between the automated method and experts was similar to the error between the two experts.

    Conclusions:

    • Automated ONSD measurement via image processing is a viable, accurate, and efficient alternative to manual methods.
    • This technique has the potential to improve the prediction of increased ICP, reducing healthcare costs and patient burden.