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• The proposed detection-gated pipeline integrates a YOLOv8-based detector with a U-Net segmenter for glottal segmentation.method 95%
• The pipeline achieved state-of-the-art performance on the GIRAFE benchmark with a Dice Similarity Coefficient (DSC) of 0.81.result 95%
• The model demonstrated superior generalizability on the BAGLS dataset with a DSC of 0.85 without institutional fine-tuning.result 95%
• Automated kinematic features, such as the coefficient of variation (CV) of the glottal area, can distinguish between healthy and pathological vocal function.result 90%
• The detection-gated architecture is computationally efficient, achieving approximately 35 frames per second for real-time clinical use.technical 90%
• The approach depends on the quality and consistency of videoendoscopic images, with potential limitations in extremely varied conditions or hardware not covered by the datasets.limitation 85%
• The market potential for this technology spans ENT specialists and hospitals, driven by the growing demand for non-invasive diagnostic tools.market 80%

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