Motion adaptive patch-based low-rank approach for compressed sensing cardiac cine MRI

Huisu Yoon, Kyung Sang Kim, Daniel Kim, Yoram Bresler, Jong Chul Ye*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

41 Scopus citations

Abstract

One of the technical challenges in cine magnetic resonance imaging (MRI) is to reduce the acquisition time to enable the high spatio-temporal resolution imaging of a cardiac volume within a short scan time. Recently, compressed sensing approaches have been investigated extensively for highly accelerated cine MRI by exploiting transform domain sparsity using linear transforms such as wavelets, and Fourier. However, in cardiac cine imaging, the cardiac volume changes significantly between frames, and there often exist abrupt pixel value changes along time. In order to effectively sparsify such temporal variations, it is necessary to exploit temporal redundancy along motion trajectories. This paper introduces a novel patch-based reconstruction method to exploit geometric similarities in the spatio-temporal domain. In particular, we use a low rank constraint for similar patches along motion, based on the observation that rank structures are relatively less sensitive to global intensity changes, but make it easier to capture moving edges. A Nash equilibrium formulation with relaxation is employed to guarantee convergence. Experimental results show that the proposed algorithm clearly reconstructs important anatomical structures in cardiac cine image and provides improved image quality compared to existing state-of-the-art methods such as k-t FOCUSS, k-t SLR, and MASTeR.

Original languageEnglish (US)
Article number6832623
Pages (from-to)2069-2085
Number of pages17
JournalIEEE Transactions on Medical Imaging
Volume33
Issue number11
DOIs
StatePublished - Nov 1 2014

Keywords

  • Compressed sensing dynamic magnetic resonance imaging (MRI)
  • Nash equilibrium
  • generalized Huber approximation
  • multiple object functions
  • overlapped patches
  • patch-based low-rank
  • proximal mapping
  • rank penalty
  • relaxation

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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