Computationally efficient deep neural network for computed tomography image reconstruction
Purpose Deep neural network‐based image reconstruction has demonstrated promising
performance in medical imaging for undersampled and low‐dose scenarios. However, it …
performance in medical imaging for undersampled and low‐dose scenarios. However, it …
Computationally efficient deep neural network for computed tomography image reconstruction.
D Wu, K Kim, Q Li - Medical Physics, 2019 - europepmc.org
Purpose Deep neural network-based image reconstruction has demonstrated promising
performance in medical imaging for undersampled and low-dose scenarios. However, it …
performance in medical imaging for undersampled and low-dose scenarios. However, it …
Computationally Efficient Deep Neural Network for Computed Tomography Image Reconstruction
D Wu, K Kim, Q Li - arXiv preprint arXiv:1810.03999, 2018 - arxiv.org
Deep-neural-network-based image reconstruction has demonstrated promising
performance in medical imaging for under-sampled and low-dose scenarios. However, it …
performance in medical imaging for under-sampled and low-dose scenarios. However, it …
Computationally efficient deep neural network for computed tomography image reconstruction
D Wu, K Kim, Q Li - Medical Physics, 2019 - ui.adsabs.harvard.edu
PurposeDeep neural network‑based image reconstruction has demonstrated promising
performance in medical imaging for undersampled and low‑dose scenarios. However, it …
performance in medical imaging for undersampled and low‑dose scenarios. However, it …
Computationally efficient deep neural network for computed tomography image reconstruction
D Wu, K Kim, Q Li - Medical physics, 2019 - pubmed.ncbi.nlm.nih.gov
Purpose Deep neural network-based image reconstruction has demonstrated promising
performance in medical imaging for undersampled and low-dose scenarios. However, it …
performance in medical imaging for undersampled and low-dose scenarios. However, it …