Improving subspace constrained radial fast spin echo MRI using block matching driven non-local low rank regularization

Sagar Mandava, Mahesh B. Keerthivasan, Diego R. Martin, Maria I. Altbach, Ali Bilgin

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Subspace-constrained reconstruction methods restrict the relaxation signals (of size M) in the scene to a pre-determined subspace (of size K≪M) and allow multi-contrast imaging and parameter mapping from accelerated acquisitions. However, these constraints yield poor image quality at some imaging contrasts, which can impact the parameter mapping performance. Additional regularization such as the use of joint-sparse (JS) or locally-low-rank (LLR) constraints can help improve the recovery of these images but are not sufficient when operating at high acceleration rates. We propose a method, non-local rank 3D (NLR3D), that is built on block matching and transform domain low rank constraints to allow high quality recovery of subspace-coefficient images (SCI) and subsequent multi-contrast imaging and parameter mapping. The performance of NLR3D was evaluated using Monte-Carlo (MC) simulations and compared against the JS and LLR methods. In vivo T 2 mapping results are presented on brain and knee datasets. MC results demonstrate improved bias, variance, and MSE behavior in both the multi-contrast images and parameter maps when compared to the JS and LLR methods. In vivo brain and knee results at moderate and high acceleration rates demonstrate improved recovery of high SNR early TE images as well as parameter maps. No significant difference was found in the T2 values measured in ROIs between the NLR3D reconstructions and the reference images (Wilcoxon signed rank test). The proposed method, NLR3D, enables recovery of high-quality SCI and, consequently, the associated multi-contrast images and parameter maps.

Original languageEnglish (US)
Article number04NT03
Pages (from-to)04NT03
JournalPhysics in Medicine and Biology
Issue number4
StatePublished - Feb 11 2021


  • Accelerated imaging
  • Block matching
  • Image reconstruction
  • Multi-contrast mri
  • Non-local low rank
  • Parameter mapping
  • Subspace-constraint
  • Knee/diagnostic imaging
  • Humans
  • Magnetic Resonance Imaging/methods
  • Brain/diagnostic imaging
  • Algorithms
  • Sensitivity and Specificity
  • Image Processing, Computer-Assisted/methods
  • Image Enhancement/methods
  • Monte Carlo Method

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging


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