A Deep Learning Based Anti-aliasing Self Super-Resolution Algorithm for MRI-Reference-Cited by-同舟云学术

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A Deep Learning Based Anti-aliasing Self Super-Resolution Algorithm for MRI

Published:2018 Issue: Volume: Page:100-108
ISSN:0302-9743
Container-title:Medical Image Computing and Computer Assisted Intervention – MICCAI 2018
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Author:

Zhao Can,Carass Aaron,Dewey Blake E.,Woo Jonghye,Oh Jiwon,Calabresi Peter A.,Reich Daniel S.,Sati Pascal,Pham Dzung L.,Prince Jerry L.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-00928-1_12

Reference16 articles.

1. Delbracio, M., Sapiro, G.: Hand-held video deblurring via efficient Fourier aggregation. IEEE Trans. Comput. Imaging 1(4), 270–283 (2015)

2. Greenspan, H.: Super-resolution in medical imaging. Comput. J. 52(1), 43–63 (2008)

3. Huang, J.B., Singh, A., Ahuja, N.: Single image super-resolution from transformed self-exemplars. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2015

4. Lecture Notes in Computer Science;A Jog,2016

5. Kim, J., Kwon Lee, J., Lee, K.: Accurate image super-resolution using very deep convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1646–1654 (2016)

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