Super-resolution reconstruction of single anisotropic 3D MR images using residual convolutional neural network-Reference-Cited by-同舟云学术

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Super-resolution reconstruction of single anisotropic 3D MR images using residual convolutional neural network

Published:2020-06 Issue: Volume:392 Page:209-220
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Du Jinglong,He Zhongshi,Wang Lulu,Gholipour Ali,Zhou Zexun,Chen Dingding,Jia Yuanyuan

Funder

National Natural Science Foundation of China

Graduate Research and Innovation Foundation of Chongqing, China

China Postdoctoral Science Foundatio

Chongqing Medical University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference37 articles.

1. Image super-resolution survey;Van Ouwerkerk;Image Vis. Comput.,2006

2. Super-resolution in medical imaging;Greenspan;Comput. J.,2008

3. Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI;Gholipour;Med. Phys.,2015

4. Single anisotropic 3-D MR image upsampling via overcomplete dictionary trained from in-plane high resolution slices;Jia;IEEE J. Biomed. Health Inform.,2016

5. A new sparse representation framework for reconstruction of an isotropic high spatial resolution MR volume from orthogonal anisotropic resolution scans;Jia;IEEE Trans. Med. Imaging,2017

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