Conditional Generative Adversarial Networks for Metal Artifact Reduction in CT Images of the Ear

We propose an approach based on a conditional generative adversarial network (cGAN) for the reduction of metal artifacts (RMA) in computed tomography (CT) ear images of cochlear implants (CIs) recipients. Our training set contains paired pre-implantation and post-implantation CTs of 90 ears. At the...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Jg. 11070; S. 3
Hauptverfasser:	Wang, Jianing, Zhao, Yiyuan, Noble, Jack H, Dawant, Benoit M
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Germany 01.01.2018
Schlagworte:	Algorithms Cochlea - diagnostic imaging Humans Metals Radiographic Image Enhancement Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Sensitivity and Specificity Tomography, X-Ray Computed Metal Artifact Reduction Conditional Generative Adversarial Networks Cochlear Implants
Online-Zugang:	Weitere Angaben
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!