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

Jucheng Zhang1, Yonghua Chu2, Wenhong Ding3

  • 1Department of Clinical Engineering, 2nd Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China. jucheng@zju.edu.cn.

BMC Medical Imaging
|April 5, 2019
PubMed
Summary
This summary is machine-generated.

High-pass filtered SENSE (HF-SENSE) improves MRI speed by reducing noise and artifacts. This new method enhances image quality, allowing for higher acceleration factors in clinical applications.

Keywords:
Artificial sparsityHigh pass filterImage reconstructionSENSE

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Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging Technology

Background:

  • MRI acquisition speed is a major limitation.
  • Partially parallel imaging (PPI) methods like SENSE accelerate data acquisition.
  • Standard SENSE suffers from artifacts at higher reduction factors.

Purpose of the Study:

  • To improve the SENSE method for faster MRI acquisition.
  • To reduce aliasing artifacts and noise in SENSE reconstructions.
  • To enhance the clinical applicability of SENSE through improved image quality.

Main Methods:

  • Applied a high-pass filter to raw k-space data for sensitivity estimation and undersampling.
  • Utilized adaptive array coil combination for block-by-block sensitivity map calculation.
  • Reconstructed images using Tikhonov-regularized SENSE and applied an inverse filter in k-space.

Main Results:

  • HF-SENSE significantly reduces the noise level in reconstructed MRI images compared to standard SENSE.
  • The proposed HF-SENSE method achieves a lower normalized root-mean-square error (NRMSE).
  • Both simulation and in vivo experiments validate the effectiveness of HF-SENSE.

Conclusions:

  • HF-SENSE effectively exploits artificial sparsity using a high-pass filter to enhance SENSE performance.
  • The method improves image quality and enables higher acceleration factors.
  • HF-SENSE offers improved clinical applicability for SENSE-based MRI.