A dataset of over 18,000 surgical images demonstrates AI's feasibility in identifying the recurrent laryngeal nerve during thyroid surgery.
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The recurrent laryngeal nerve is at risk of injury in 3% to 8% of thyroidectomies, potentially leading to serious complications.
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The ThyRLN-PUMCH dataset includes images from 28 patients and reflects various intraoperative conditions encountered in surgery.
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DeepLabV3+ and Mask2Former models were tested, achieving 64% and 67% recall, respectively, with Mask2Former showing improved precision.
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The study highlights the need for further research to enhance AI's accuracy in detecting nerve structures during thyroid surgeries.
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