Difference between revisions of "ISMORE"
Jump to navigation
Jump to search
(Typoe.) |
(Force some spacing.) |
||
| Line 3: | Line 3: | ||
{{TOCright}} | {{TOCright}} | ||
<u>S</u>ynthetic <u>M</u>ulti-<u>O</u>rientation <u>R</u>esolution <u>E</u>nhancement (SMORE) and its iterative variant (iSMORE) are single image super-resolution techniques. Some of the associated publications are: | <u>S</u>ynthetic <u>M</u>ulti-<u>O</u>rientation <u>R</u>esolution <u>E</u>nhancement (SMORE) and its iterative variant (iSMORE) are single image super-resolution techniques. Some of the associated publications are: | ||
| + | {{-}} | ||
{{iacl-pub| author = C Zhao, B.E. Dewey, D.L. Pham, P.A. Calabresi, D.S. Reich, and J.L. Prince| title = SMORE: A Self-supervised Anti-aliasing and Super-resolution Algorithm for MRI Using Deep Learning| jrnl = tmi| number = 40(3):805-817| when = 2021| doi = 10.1109/TMI.2020.3037187}} | {{iacl-pub| author = C Zhao, B.E. Dewey, D.L. Pham, P.A. Calabresi, D.S. Reich, and J.L. Prince| title = SMORE: A Self-supervised Anti-aliasing and Super-resolution Algorithm for MRI Using Deep Learning| jrnl = tmi| number = 40(3):805-817| when = 2021| doi = 10.1109/TMI.2020.3037187}} | ||
{{iacl-pub| author = C. Zhao, M. Shao, A. Carass, H. Li, B.E. Dewey, L.M. Ellingsen, J. Woo, M.A. Guttman, A.M. Blitz, M. Stone, P.A. Calabresi, H. Halperin, and J.L. Prince | title = Applications of a deep learning method for anti-aliasing and super-resolution in MRI | jrnl = mrm| number = 64:132-141| when = 2019| doi = 10.1016/j.mri.2019.05.038| pubmed = 31247254}} | {{iacl-pub| author = C. Zhao, M. Shao, A. Carass, H. Li, B.E. Dewey, L.M. Ellingsen, J. Woo, M.A. Guttman, A.M. Blitz, M. Stone, P.A. Calabresi, H. Halperin, and J.L. Prince | title = Applications of a deep learning method for anti-aliasing and super-resolution in MRI | jrnl = mrm| number = 64:132-141| when = 2019| doi = 10.1016/j.mri.2019.05.038| pubmed = 31247254}} | ||
Revision as of 18:49, 4 March 2021
<meta name="title" content="SMORE & iSMORE: Single Image Super-Resolution"/>
Synthetic Multi-Orientation Resolution Enhancement (SMORE)
Synthetic Multi-Orientation Resolution Enhancement (SMORE) and its iterative variant (iSMORE) are single image super-resolution techniques. Some of the associated publications are:
- C Zhao, B.E. Dewey, D.L. Pham, P.A. Calabresi, D.S. Reich, and J.L. Prince, "SMORE: A Self-supervised Anti-aliasing and Super-resolution Algorithm for MRI Using Deep Learning", IEEE Trans. Med. Imag., 40(3):805-817, 2021.
- C. Zhao, M. Shao, A. Carass, H. Li, B.E. Dewey, L.M. Ellingsen, J. Woo, M.A. Guttman, A.M. Blitz, M. Stone, P.A. Calabresi, H. Halperin, and J.L. Prince, "Applications of a deep learning method for anti-aliasing and super-resolution in MRI", Mag. Reson. Im., 64:132-141, 2019. (PubMed)
- C. Zhao, S. Son, Y. Kim, and J.L. Prince, "iSMORE: An Iterative Self Super-Resolution Algorithm", pp. 130-139, Simulation and Synthesis in Medical Imaging (SASHIMI 2019) held in conjunction with the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), Shenzhen, China, October 13–17, 2019.
| iSMORE | |
| Singularity image | 1.6GB |
| Shell script | 2KB |
| License (GPL v3.0) | 35k |
Specifying a single iteration within the shell script is equivalent to running SMORE. If you use the code in anyway please cite some of our papers.
