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Related Experiment Video

Updated: Feb 12, 2026

Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction
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Respiratory Motion Correction for Compressively Sampled Free Breathing Cardiac MRI Using Smooth l1-Norm

Muhammad Bilal1, Jawad Ali Shah2, Ijaz M Qureshi3

  • 1Electrical Engineering Department, International Islamic University, Islamabad, Islamabad, Pakistan.

International Journal of Biomedical Imaging
|April 4, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a two-step method to improve cardiac MRI quality by reducing acquisition time and correcting respiratory motion. The technique enhances image clarity and diagnostic accuracy for free-breathing scans.

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Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Signal Processing

Background:

  • Magnetic Resonance Imaging (MRI) acquisition time is reduced using compressed sensing (CS) and transformed domain sparsity.
  • Respiratory motion during MRI scans causes significant image artifacts like blurring and ghosting.
  • Accurate motion estimation and correction are crucial for high-quality recovered MR images.

Purpose of the Study:

  • To propose a novel two-step framework for recovering cardiac MRI images.
  • To address image quality degradation caused by free-breathing respiratory motion.
  • To enhance the diagnostic utility of accelerated cardiac MRI.

Main Methods:

  • Image recovery using an optimization problem with gradient descent and a hyperbolic tangent approximation of the L1-norm regularizer.
  • Respiratory motion estimation and correction utilizing the Adaptive Rood Pattern Search (ARPS) block matching algorithm.
  • Validation on simulated and in vivo 2D cardiac cine MRI data with varying acceleration factors.

Main Results:

  • The proposed method demonstrated improved Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR), and Mean Square Error (MSE) in simulations.
  • Comparative analysis showed superior performance against k-t FOCUSS with Motion Estimation and Motion Correction (MEMC).
  • Successful application to free-breathing cardiac cine MRI data.

Conclusions:

  • The developed two-step approach effectively recovers cardiac MR images under respiratory motion.
  • The method significantly reduces artifacts and improves image quality in accelerated MRI.
  • This technique offers a promising solution for enhanced cardiac MRI diagnostics in free-breathing conditions.