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

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...

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Bibliographic Details
Main Authors: Chang Liu, Xi Wu, Xi Yu, YuanYan Tang, Jian Zhang, JiLiu Zhou
Format: Article
Language:English
Published: BMC 2018-08-01
Series:BioMedical Engineering OnLine
Subjects:
Super-resolution reconstruction
Multi-scale information fusion
Convolution network
Magnetic resonance imaging
Online Access:http://link.springer.com/article/10.1186/s12938-018-0546-9

Internet

http://link.springer.com/article/10.1186/s12938-018-0546-9

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