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Motion correction based reconstruction method for compressively sampled cardiac MR imaging.
Magn Reson Imaging 2017; 36:159-166MR

Abstract

Respiratory motion during Magnetic Resonance (MR) acquisition causes strong blurring artifacts in the reconstructed images. These artifacts become more pronounced when used with the fast imaging reconstruction techniques like compressed sensing (CS). Recently, an MR reconstruction technique has been done with the help of compressed sensing (CS), to provide good quality sparse images from the highly under-sampled k-space data. In order to maximize the benefits of CS, it is obvious to use CS with the motion corrected samples. In this paper, we propose a novel CS based motion corrected image reconstruction technique. First, k-space data have been assigned to different respiratory state with the help of frequency domain phase correlation method. Then, multiple sparsity constraints has been used to provide good quality reconstructed cardiac cine images with the highly under-sampled k-space data. The proposed method exploits the multiple sparsity constraints, in combination with demon based registration technique and a novel reconstruction technique to provide the final motion free images. The proposed method is very simple to implement in clinical settings as compared to existing motion corrected methods. The performance of the proposed method is examined using simulated data and clinical data. Results show that this method performs better than the reconstruction of CS based method of cardiac cine images. Different acceleration rates have been used to show the performance of the proposed method.

Authors+Show Affiliations

Department of Electrical Engineering, Air University Islamabad, Pakistan. Electronic address: haseeb@mail.au.edu.pk.Department of Electrical Engineering, Air University Islamabad, Pakistan.Department of Electronic Engineering, Faculty of Engineering & Technology International Islamic University, Islamabad, Pakistan.Department of Electrical Engineering, Air University Islamabad, Pakistan.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

27746392

Citation

Ahmed, Abdul Haseeb, et al. "Motion Correction Based Reconstruction Method for Compressively Sampled Cardiac MR Imaging." Magnetic Resonance Imaging, vol. 36, 2017, pp. 159-166.
Ahmed AH, Qureshi IM, Shah JA, et al. Motion correction based reconstruction method for compressively sampled cardiac MR imaging. Magn Reson Imaging. 2017;36:159-166.
Ahmed, A. H., Qureshi, I. M., Shah, J. A., & Zaheer, M. (2017). Motion correction based reconstruction method for compressively sampled cardiac MR imaging. Magnetic Resonance Imaging, 36, pp. 159-166. doi:10.1016/j.mri.2016.10.008.
Ahmed AH, et al. Motion Correction Based Reconstruction Method for Compressively Sampled Cardiac MR Imaging. Magn Reson Imaging. 2017;36:159-166. PubMed PMID: 27746392.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Motion correction based reconstruction method for compressively sampled cardiac MR imaging. AU - Ahmed,Abdul Haseeb, AU - Qureshi,Ijaz M, AU - Shah,Jawad Ali, AU - Zaheer,Muhammad, Y1 - 2016/10/14/ PY - 2016/05/14/received PY - 2016/09/26/revised PY - 2016/10/05/accepted PY - 2016/10/18/pubmed PY - 2017/8/8/medline PY - 2016/10/18/entrez KW - Cardiac cine MRI KW - Compressed sensing KW - Motion correction KW - Non-rigid motion KW - Under-sampling SP - 159 EP - 166 JF - Magnetic resonance imaging JO - Magn Reson Imaging VL - 36 N2 - Respiratory motion during Magnetic Resonance (MR) acquisition causes strong blurring artifacts in the reconstructed images. These artifacts become more pronounced when used with the fast imaging reconstruction techniques like compressed sensing (CS). Recently, an MR reconstruction technique has been done with the help of compressed sensing (CS), to provide good quality sparse images from the highly under-sampled k-space data. In order to maximize the benefits of CS, it is obvious to use CS with the motion corrected samples. In this paper, we propose a novel CS based motion corrected image reconstruction technique. First, k-space data have been assigned to different respiratory state with the help of frequency domain phase correlation method. Then, multiple sparsity constraints has been used to provide good quality reconstructed cardiac cine images with the highly under-sampled k-space data. The proposed method exploits the multiple sparsity constraints, in combination with demon based registration technique and a novel reconstruction technique to provide the final motion free images. The proposed method is very simple to implement in clinical settings as compared to existing motion corrected methods. The performance of the proposed method is examined using simulated data and clinical data. Results show that this method performs better than the reconstruction of CS based method of cardiac cine images. Different acceleration rates have been used to show the performance of the proposed method. SN - 1873-5894 UR - https://www.unboundmedicine.com/medline/citation/27746392/Motion_correction_based_reconstruction_method_for_compressively_sampled_cardiac_MR_imaging_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0730-725X(16)30155-2 DB - PRIME DP - Unbound Medicine ER -