Morphological component analysis based compressed sensing technique on dynamic MRI reconstruction

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

Abstract

Compressive sensing (CS) MRI have been developed to speed up data acquisition without significantly degrading image quality. This paper proposes a novel compressed sensing reconstruction method exploiting temporally complementary morphological characteristics. This method relies on some well-developed signal processing techniques: Morphological component analysis (MCA) and sparse derivatives. It also relies on well-developed MRI reconstruction techniques: Incoherent undersampling schemes and parallel imaging. Other MRI schemes were simulated to make comparsion with our MCA-based CS method. CS and parallel imaging has been merged together to highly increase acceleration rate. This work simulates this framework also. Performance of applying different temporal regularizations individually and hybrid signal models based on MCA with and without auxilary spatial regularization are all analyzed in this paper. Nonlinear conjugate gradient algorithm is applied to gain all signal components simultaneously.

Original languageEnglish (US)
Title of host publication2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509067138
DOIs
StatePublished - Feb 7 2017
Event2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Philadelphia, United States
Duration: Dec 3 2016 → …

Publication series

Name2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings

Other

Other2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016
CountryUnited States
CityPhiladelphia
Period12/3/16 → …

Keywords

  • Compressed Sensing
  • Morphological Component Analysis
  • Parallel Imaging
  • Sparse Derivatives

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering

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  • Cite this

    Yin, L., & Selesnick, I. (2017). Morphological component analysis based compressed sensing technique on dynamic MRI reconstruction. In 2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings [7846881] (2016 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPMB.2016.7846881