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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...

पूर्ण विवरण

में बचाया:
ग्रंथसूची विवरण
में प्रकाशित:Med Image Comput Comput Assist Interv
मुख्य लेखकों: Wang, Jianing, Zhao, Yiyuan, Noble, Jack H., Dawant, Benoit M.
स्वरूप: Artigo
भाषा:Inglês
प्रकाशित: 2018
विषय:
ऑनलाइन पहुंच: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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