HF-SENSE: an improved partially parallel imaging using a high-pass filter

Jucheng Zhang, Yonghua Chu, Wenhong Ding, Liyi Kang, Ling Xia, Sanjay Jaiswal, Zhikang Wang, Zhifeng Chen

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

Background: One of the major limitations of MRI is its slow acquisition speed. To accelerate data acquisition, partially parallel imaging (PPI) methods have been widely used in clinical applications such as sensitivity encoding (SENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA). SENSE is a popular image-domain partially parallel imaging method, which suffers from residual aliasing artifacts when the reduction factor goes higher. Undersampling the k-space data and then reconstruct images with artificial sparsity is an efficient way to accelerate data acquisition. By exploiting artificial sparsity with a high-pass filter, an improved SENSE method is proposed in this work, termed high-pass filtered SENSE (HF-SENSE). Methods: First, a high-pass filter was applied to the raw k-space data, the result of which was used as the inputs of sensitivity estimation and undersampling process. Second, the adaptive array coil combination method was adopted to calculate sensitivity maps on a block-by-block basis. Third, Tikhonov regularized SENSE was then used to reconstruct magnetic resonance images. Fourth, the reconstructed images were transformed into k-space data, which was filtered with the corresponding inverse filter. Results: Both simulation and in vivo experiments demonstrate that HF-SENSE method significantly reduces noise level of the reconstructed images compared with SENSE. Furthermore, it is found that HF-SENSE can achieve lower normalized root-mean-square error value than SENSE. Conclusions: The proposed method explores artificial sparsity with a high-pass filter. Experiments demonstrate that the proposed HF-SENSE method can improve the image quality of SENSE reconstruction. The high-pass filter parameters can be predefined. With this image reconstruction method, high acceleration factors can be achieved, which will improve the clinical applicability of SENSE. This retrospective study (HF-SENSE: an improved partially parallel imaging using a high-pass filter) was approved by Institute Review Board of 2nd Affiliated Hospital of Zhejiang University (ethical approval number 2018-314). Participant for all images have informed consent that he knew the risks and agreed to participate in the research.

Original languageEnglish
Article number27
Number of pages10
JournalBMC Medical Imaging
Volume19
Issue number1
DOIs
Publication statusPublished - 3 Apr 2019
Externally publishedYes

Keywords

  • Artificial sparsity
  • High pass filter
  • Image reconstruction
  • SENSE

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