Fusing multi-scale information in convolution network for MR image super-resolution reconstruction-Reference-Cited by-同舟云学术

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

Published:2018-08-25 Issue:1 Volume:17 Page:
ISSN:1475-925X
Container-title:BioMedical Engineering OnLine
language:en
Short-container-title:BioMed Eng OnLine

Author:

Liu Chang^ORCID,Wu Xi,Yu Xi,Tang YuanYan,Zhang Jian,Zhou JiLiu

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

The Educational Commission of Sichuan Province of China

Publisher

Springer Science and Business Media LLC

Subject

Radiology Nuclear Medicine and imaging,Biomedical Engineering,General Medicine,Biomaterials,Radiological and Ultrasound Technology

Link

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

Reference38 articles.

1. Thévenaz P, Blu T, Unser M. Interpolation revisited medical images application. IEEE Trans Med Imag. 2000;19(7):739–58.

2. Lehmann TM, Gönner C, Spitzer K. Survey: interpolation methods in medical image processing. IEEE Trans Med Imag. 1999;18(11):1049–75.

3. Shilling RZ, Robbie TQ, Bailloeul T, Mewes K, Mersereau RM, Brummer ME. A super-resolution framework for 3-d high-resolution and high-contrast imaging using 2-d multislice MRI. IEEE Trans Med Imag. 2009;28(5):633–44.

4. Herment A, Roullot E, Bloch I, Jolivet O, De Cesare A, Frouin F, Bittoun J, Mousseaux E. Local reconstruction of stenosed sections of artery using multiple MRA acquisitions. Magn Reson Med. 2003;49(4):731–42.

5. Peled S, Yeshurun Y. Superresolution in MRI: application to human white matter fiber tract visualization by diffusion tensor imaging. Magn Reson Med. 2001;45(1):29–35.

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