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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Detalles Bibliográficos
Autores principales: Heilemann, Gerd, Matthewman, Mark, Kuess, Peter, Goldner, Gregor, Widder, Joachim, Georg, Dietmar, Zimmermann, Lukas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Short Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9948880/
https://www.ncbi.nlm.nih.gov/pubmed/34930685
http://dx.doi.org/10.1016/j.zemedi.2021.11.006

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9948880/
https://www.ncbi.nlm.nih.gov/pubmed/34930685
http://dx.doi.org/10.1016/j.zemedi.2021.11.006

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