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Colonoscopy is the third leading cause of cancer deaths worldwide. While automated segmentation methods can help detect polyps and consequently improve their surgical removal, the clinical usability of these methods requires a trade-off between accuracy and speed. In this work, we exploit the traditional U-Net methods and compare different segmentation-loss functions. Our results demonstrate that IoU loss results in an improved segmentation performance (nearly 3% improvement on Dice) for real-time polyp segmentation.


Conference paper

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