Fusing multi-scale information in convolution network for MR image super-resolution reconstruction
Abstract Background Magnetic resonance (MR) images are usually limited by low spatial resolution, which leads to errors in post-processing procedures. Recently, learning-based super-resolution methods, such as sparse coding and super-resolution convolution neural network, have achieved promising rec...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2018-08-01
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Series: | BioMedical Engineering OnLine |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s12938-018-0546-9 |