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Augmentation of CBCT Reconstructed from Under-sampled Projections using Deep Learning
Edges tend to be over-smoothed in total variation (TV) regularized under-sampled images. In this study, symmetric residual convolutional neural network (SR-CNN), a deep learning based model, was proposed to enhance the sharpness of edges and detailed anatomical structures in under-sampled CBCT. For...
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| Pubblicato in: | IEEE Trans Med Imaging |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6812588/ https://ncbi.nlm.nih.gov/pubmed/31021791 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2019.2912791 |
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