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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...
Gorde:
| Argitaratua izan da: | Med Image Comput Comput Assist Interv |
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| Egile Nagusiak: | , , , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
2018
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6347117/ https://ncbi.nlm.nih.gov/pubmed/30693351 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-00928-1_1 |
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