Magnetic resonance image reconstruction using similarities learnt from multi-modal images

Xiaobo Qu, Yingkun Hou, Fan Lam, Di Guo, Zhong Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Compressed sensing has shown great potential to speed up magnetic resonance imaging (MRI) assuming the image is sparse and compressible in a transform domain. Conventional methods typically use a pre-defined sparsifying transform such as wavelets or finite difference, which sometimes does not lead to a sufficient sparse representation. In this paper, we design a patch-based nonlocal operator (PANO) to model the sparsity between image patches. The linearity of PANO allows us to establish a general formulation to reconstruct magnetic resonance image from undersampled data and provides feasibility to incorporate prior information learnt from guide images. To demonstrate the feasibility and performance of PANO, learning similarities from multi-modal images are presented to significantly improve the reconstructed images over conventional redundant wavelets in terms of visual quality and reconstruction errors.

Original languageEnglish (US)
Title of host publication2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings
Pages264-268
Number of pages5
DOIs
StatePublished - Dec 11 2013
Event2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Beijing, China
Duration: Jul 6 2013Jul 10 2013

Publication series

Name2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings

Other

Other2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013
CountryChina
CityBeijing
Period7/6/137/10/13

Keywords

  • Fast imaging
  • MRI
  • compressed sensing
  • multi-modality
  • nonlocal operator

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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  • Cite this

    Qu, X., Hou, Y., Lam, F., Guo, D., & Chen, Z. (2013). Magnetic resonance image reconstruction using similarities learnt from multi-modal images. In 2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings (pp. 264-268). [6625341] (2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013 - Proceedings). https://doi.org/10.1109/ChinaSIP.2013.6625341