Difference between revisions of "ISMORE"

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<u>S</u>ynthetic <u>M</u>ulti-<u>O</u>rientation <u>R</u>esolution <u>E</u>nhancement&nbsp;(SMORE) and its iterative variant (iSMORE) are single image super-resolution techniques. Some of the associated publication are:
 
<u>S</u>ynthetic <u>M</u>ulti-<u>O</u>rientation <u>R</u>esolution <u>E</u>nhancement&nbsp;(SMORE) and its iterative variant (iSMORE) are single image super-resolution techniques. Some of the associated publication are:
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{{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|jnrl=tmi|number=''IN PRESS''|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}}
{{iacl-pub|author=C. Zhao, S. Son, Y. Kim, and J.L. Prince|title=iSMORE: An Iterative Self Super-Resolution Algorithm|when=Simulation and Synthesis in Medical Imaging (SASHIMI&nbsp;2019) held in conjunction with the {{iacl-pub miccai2019}}|number=130-139|period=|doi=10.1007/978-3-030-32778-1_14}}
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{{iacl-pub|author=C. Zhao, S. Son, Y. Kim, and J.L. Prince|title=iSMORE: An Iterative Self Super-Resolution Algorithm|when=Simulation and Synthesis in Medical Imaging (SASHIMI&nbsp;2019) held in conjunction with the {{iacl-pub miccai2019}}|number=pp. 130-139|period=|doi=10.1007/978-3-030-32778-1_14}}
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{|align="center" style="width:75%; border:2px #e99095 solid; background:#ffffff; text-align:left;"
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|-
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| colspan="2" align="center" | '''iSMORE'''
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|-
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| {{iacl|~aaron/iSMORE/ismore-2019-2020_Jan_18.simg|Singularity image}}
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| 1.6GB
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|-
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| {{iacl|~aaron/iSMORE/run_singularity_iSMORE.sh|Shell script}}
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| 2KB
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|-
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| {{iacl|~aaron/iSMORE/gpl-3.0.txt|License (GPL v3.0)}}
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| 35k
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|-
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|}
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Specifying a single iteration within the shell script is equivalent to run SMORE. If you use the code in anyway please cite some of our papers.

Revision as of 03:54, 19 January 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 publication 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", IN PRESS, 2021. (doi)
  • 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", Magnetic Resonance in Medicine, 64:132-141, 2019. (doi) (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. (doi)


iSMORE
Singularity image 1.6GB
Shell script 2KB
License (GPL v3.0) 35k

Specifying a single iteration within the shell script is equivalent to run SMORE. If you use the code in anyway please cite some of our papers.