Artificial Intelligence–Assisted Indocyanine Green Angiography for Perforators Identification in the Anterolateral Thigh Flap

Abstract

AI-assisted ICG angiography is an emerging tool with potential to support perforator mapping. Although the current AI model demonstrated limited sensitivity, its accuracy can be enhanced by expanding training datasets, integrating temporal fluorescence dynamics, and refining fluorescence-time curve analysis. Future advancements in AI-driven image processing may further optimize intraoperative perforator identification, ultimately improving surgical precision and patient outcomes.

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