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Unsupervised Domain Adaptation for Automatic Polyp Segmentation Using Synthetic Data

Colorectal cancer is a significant health concern that can often be prevented through early detection of precancerous polyps during routine screenings. Although artificial intelligence (AI) methods have shown potential in reducing polyp miss rates, clinical adoption remains limited due to concerns o...

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Main Authors: Ioanna Malli, Ioannis A. Vezakis, Ioannis Kakkos, Theodosis Kalamatianos, George K. Matsopoulos
Format: Artigo
Language:Inglês
Published: MDPI AG 2025-09-01
Series:Applied Sciences
Subjects:
unsupervised domain adaptation
polyp segmentation
domain shift
mix vision transformer
self-training
synthetic medical data
Online Access:https://www.mdpi.com/2076-3417/15/17/9829
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