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Abstract Objective Colon polyp detection is crucial in reducing the incidence of colorectal cancer. However, due to the diverse morphology of colon polyps, their high similarity to surrounding tissues, and the difficulty of detecting small target polyps, false negatives and false positives are common problems. Methods To address this, we propose a lightweight and efficient colon polyp detection model based on YOLOv10, a deep learning-based object detection method—EP-YOLO (Efficient for Polyp).
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