[HTML][HTML] Fusing multi-scale information in convolution network for MR image super-resolution reconstruction

C Liu, X Wu, X Yu, YY Tang, J Zhang… - Biomedical engineering …, 2018 - Springer
Background Magnetic resonance (MR) images are usually limited by low spatial resolution,
which leads to errors in post-processing procedures. Recently, learning-based super …

[HTML][HTML] Fusing multi-scale information in convolution network for MR image super-resolution reconstruction

C Liu, X Wu, X Yu, YY Tang… - BioMedical …, 2018 - biomedical-engineering-online …
Magnetic resonance (MR) images are usually limited by low spatial resolution, which leads
to errors in post-processing procedures. Recently, learning-based super-resolution …

Fusing multi-scale information in convolution network for MR image super-resolution reconstruction

C Liu, X Wu, X Yu, YY Tang, J Zhang… - Biomedical …, 2018 - search.proquest.com
Background Magnetic resonance (MR) images are usually limited by low spatial resolution,
which leads to errors in post-processing procedures. Recently, learning-based super …

[引用][C] Fusing multi-scale information in convolution network for MR image super-resolution reconstruction

C Liu, X Wu, X Yu, YY Tang, J Zhang… - BioMedical Engineering …, 2018 - cir.nii.ac.jp
Fusing multi-scale information in convolution network for MR image super-resolution
reconstruction | CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 …

Fusing multi-scale information in convolution network for MR image super-resolution reconstruction

C Liu, X Wu, X Yu, YY Tang… - Biomedical …, 2018 - pubmed.ncbi.nlm.nih.gov
Background Magnetic resonance (MR) images are usually limited by low spatial resolution,
which leads to errors in post-processing procedures. Recently, learning-based super …

Fusing multi-scale information in convolution network for MR image super-resolution reconstruction

C Liu, X Wu, X Yu, YY Tang, J Zhang… - BioMedical Engineering …, 2018 - go.gale.com
Background Magnetic resonance (MR) images are usually limited by low spatial resolution,
which leads to errors in post-processing procedures. Recently, learning-based super …

Fusing multi-scale information in convolution network for MR image super-resolution reconstruction

C Liu, X Wu, X Yu, YY Tang, J Zhang, JL Zhou - 2018 - repository.um.edu.mo
Background: Magnetic resonance (MR) images are usually limited by low spatial resolution,
which leads to errors in post-processing procedures. Recently, learning-based super …

Fusing multi-scale information in convolution network for MR image super-resolution reconstruction.

C Liu, X Wu, X Yu, Y Tang, J Zhang… - Biomedical Engineering …, 2018 - europepmc.org
Background Magnetic resonance (MR) images are usually limited by low spatial resolution,
which leads to errors in post-processing procedures. Recently, learning-based super …

[HTML][HTML] Fusing multi-scale information in convolution network for MR image super-resolution reconstruction

C Liu, X Wu, X Yu, YY Tang, J Zhang… - BioMedical Engineering …, 2018 - ncbi.nlm.nih.gov
Background Magnetic resonance (MR) images are usually limited by low spatial resolution,
which leads to errors in post-processing procedures. Recently, learning-based super …

[PDF][PDF] Fusing multi‑scale information in convolution network for MR image super‑resolution reconstruction

C Liu, X Wu, X Yu, YY Tang, J Zhang, JL Zhou - 2018 - biomedical-engineering-online …
Background A higher magnetic resonance image (MRI) resolution often results in fewer
image artifacts, such as the partial volume effect (PVE), and a higher algorithm accuracy in …