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

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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Bibliographic Details
Main Authors: Guoqin Li, Nursuriati Jamil, Raseeda Hamzah
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Information
Subjects:
semi-supervised learning
medical image segmentation
co-training
GAN
Diff-CoGAN
Online Access:https://www.mdpi.com/2078-2489/14/3/190

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