Comparative Clinical Evaluation of “Memory-Efficient” Synthetic 3D Generative Adversarial Networks (GAN) Head-to-Head to State of Art: Results on Computed Tomography of the Chest.

Generative adversarial networks (GANs) are increasingly used to generate synthetic medical images, addressing the critical shortage of annotated data for training artificial intelligence (AI) systems. This study introduces conditional random field (CRF)-GAN, a novel memory-efficient GAN architecture...

Descripción completa

Detalles Bibliográficos

Publicado en:	Journal of Imaging Informatics in Medicine pp. 1 - 14
Autores principales:	Shiri, Mahshid, Bortolotto, Chandra, Bruno, Alessandro, Consonni, Alessio, Grasso, Daniela Maria, Brizzi, Leonardo, Loiacono, Daniele, Preda, Lorenzo
Formato:	Journal Article
Publicado:	Springer Nature May2026
Acceso en línea:	Ver este registro en EBSCOhost