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Accuracy and Time Comparison Between Side-by-Side and Artificial Intelligence Overlayed Images.

Melina Cavichini, Dirk-Uwe G Bartsch, Alexandra Warter

    Ophthalmic Surgery, Lasers & Imaging Retina
    |February 13, 2023
    PubMed
    Summary

    Artificial intelligence (AI) significantly improves lesion colocalization accuracy and speed compared to traditional side-by-side methods. AI-assisted techniques reduce errors, making them superior for analyzing fundus images.

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    Area of Science:

    • Ophthalmology
    • Medical Imaging
    • Artificial Intelligence

    Background:

    • Accurate lesion localization is crucial in ophthalmology for diagnosis and treatment.
    • Traditional side-by-side (SBS) colocalization of color fundus photographs and infrared images can be time-consuming and prone to errors.

    Purpose of the Study:

    • To compare the accuracy and efficiency of an artificial intelligence (AI)-assisted colocalization technique against the conventional SBS method.
    • To evaluate the performance of AI in localizing pathological lesions between different imaging modalities.

    Main Methods:

    • Fifty-three pathological lesions in 11 eyes were analyzed using both SBS and AI overlaid methods.
    • Two specialists independently assessed lesion colocalization accuracy and time on different days, with outcomes recorded by an observer.

    Main Results:

    • The AI colocalization method demonstrated superior accuracy and speed compared to the SBS technique (P < .001).
    • AI-assisted colocalization was 37% faster, with an error rate of 0% versus 18% for SBS.

    Conclusions:

    • AI facilitates more accurate and rapid colocalization of pathological lesions in ophthalmological imaging.
    • AI-assisted techniques offer a significant advancement over conventional methods for lesion analysis.