Can Generative Adversarial Networks help to overcome the limited data problem in segmentation?

Can Generative Adversarial Networks help to overcome the limited data problem in segmentation?

Purpose: For image translational tasks, the application of deep learning methods showed that Generative Adversarial Network (GAN) architectures outperform the traditional U-Net networks, when using the same training data size. This study investigates whether this performance boost can also be expect...

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Bibliographic Details
Main Authors: Gerd Heilemann, Mark Matthewman, Peter Kuess, Gregor Goldner, Joachim Widder, Dietmar Georg, Lukas Zimmermann
Format: Article
Language:English
Published: Elsevier 2022-08-01
Series:Zeitschrift für Medizinische Physik
Subjects:
Automatic segmentation
Deep learning
Prostate cancer
Generative adversarial networks
Online Access:http://www.sciencedirect.com/science/article/pii/S0939388921001124

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http://www.sciencedirect.com/science/article/pii/S0939388921001124

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