Literature DB >> 18218546

An efficient method for dynamic magnetic resonance imaging.

Z P Liang1, P C Lauterbur.   

Abstract

Many magnetic resonance imaging applications require the acquisition of a time series of images. In conventional Fourier transform based imaging methods, each of these images is acquired independently so that the temporal resolution possible is limited by the number of spatial encodings (or data points in the Fourier space) collected, or one has to sacrifice spatial resolution for temporal resolution. Here, a generalized series based imaging technique is proposed to address this problem. This technique makes use of the fact that, in most time-sequential imaging problems, the high-resolution image morphology does not change from one image to another, and it improves imaging efficiency (and temporal resolution) over the conventional Fourier imaging methods by eliminating the repeated encodings of this stationary information. Additional advantages of the proposed imaging technique include a reduced number of radio frequency (RF) pulses for data collection, and thus lower RF power deposition. This method should prove useful for a variety of dynamic imaging applications, including dynamic studies of contrast agents and functional brain imaging.

Year:  1994        PMID: 18218546     DOI: 10.1109/42.363100

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  22 in total

1.  Reconstruction of dynamic image series from undersampled MRI data using data-driven model consistency condition (MOCCO).

Authors:  Julia V Velikina; Alexey A Samsonov
Journal:  Magn Reson Med       Date:  2014-11-14       Impact factor: 4.668

2.  Reference-guided sparsifying transform design for compressive sensing MRI.

Authors:  S Derin Babacan; Xi Peng; Xian-Pei Wang; Minh N Do; Zhi-Pei Liang
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

3.  Bi-Linear Modeling of Manifold-Data Geometry for Dynamic-MRI Recovery.

Authors:  Konstantinos Slavakis; Gaurav N Shetty; Abhishek Bose; Ukash Nakarmi; Leslie Ying
Journal:  Int Workshop Comput Adv Multisens Adapt Process       Date:  2018-03-12

4.  Strategies for inner volume 3D fast spin echo magnetic resonance imaging using nonselective refocusing radio frequency pulses.

Authors:  Dimitris Mitsouras; Robert V Mulkern; Frank J Rybicki
Journal:  Med Phys       Date:  2006-01       Impact factor: 4.071

5.  A framework for generalized reference image reconstruction methods including HYPR-LR, PR-FOCUSS, and k-t FOCUSS.

Authors:  Liyong Chen; Alexey Samsonov; Edward V R DiBella
Journal:  J Magn Reson Imaging       Date:  2011-08       Impact factor: 4.813

6.  Multi-scale Unrolled Deep Learning Framework for Accelerated Magnetic Resonance Imaging.

Authors:  Ukash Nakarmi; Joseph Y Cheng; Edgar P Rios; Morteza Mardani; John M Pauly; Leslie Ying; Shreyas S Vasanawala
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2020-05-22

7.  Optimal sampling for "Noquist" reduced-data cine magnetic resonance imaging.

Authors:  David Moratal; W Thomas Dixon; Senthil Ramamurthy; Stamatios Lerakis; W James Parks; Marijn E Brummer
Journal:  Med Phys       Date:  2013-01       Impact factor: 4.071

8.  Keyhole chemical exchange saturation transfer.

Authors:  G Varma; R E Lenkinski; E Vinogradov
Journal:  Magn Reson Med       Date:  2012-01-13       Impact factor: 4.668

9.  A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI.

Authors:  Ukash Nakarmi; Yanhua Wang; Jingyuan Lyu; Dong Liang; Leslie Ying
Journal:  IEEE Trans Med Imaging       Date:  2017-07-05       Impact factor: 10.048

10.  Removal of nuisance signals from limited and sparse 1H MRSI data using a union-of-subspaces model.

Authors:  Chao Ma; Fan Lam; Curtis L Johnson; Zhi-Pei Liang
Journal:  Magn Reson Med       Date:  2015-03-11       Impact factor: 4.668

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