An Improved Co-Training and Generative Adversarial Network (Diff-CoGAN) for Semi-Supervised Medical Image Segmentation

Semi-supervised learning is a technique that utilizes a limited set of labeled data and a large amount of unlabeled data to overcome the challenges of obtaining a perfect dataset in deep learning, especially in medical image segmentation. The accuracy of the predicted labels for the unlabeled data i...

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Auteurs principaux:	Guoqin Li, Nursuriati Jamil, Raseeda Hamzah
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2023-03-01
Collection:	Information
Sujets:	semi-supervised learning medical image segmentation co-training GAN Diff-CoGAN
Accès en ligne:	https://www.mdpi.com/2078-2489/14/3/190
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