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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. on Medical Imaging, 40(3):805-817, 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)

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.