Difference between revisions of "ISMORE"

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Revision as of 00:52, 3 July 2022

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. DOI: "SMORE: A Self-supervised Anti-aliasing and Super-resolution Algorithm for MRI Using Deep Learning"
  • 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. DOI: "Applications of a deep learning method for anti-aliasing and super-resolution in MRI" (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: An Iterative Self Super-Resolution Algorithm"


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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.