scholarly journals Compressed sensing in dynamic MRI

2008 ◽  
Vol 59 (2) ◽  
pp. 365-373 ◽  
Author(s):  
Urs Gamper ◽  
Peter Boesiger ◽  
Sebastian Kozerke
Keyword(s):  
Compressed Sensing ◽  
Dynamic Mri

scholarly journals k-t FOCUSS: A general compressed sensing framework for high resolution dynamic MRI

2008 ◽  
Vol 61 (1) ◽  
pp. 103-116 ◽  
Author(s):  
Hong Jung ◽  
Kyunghyun Sung ◽  
Krishna S. Nayak ◽  
Eung Yeop Kim ◽  
Jong Chul Ye
Keyword(s):  
High Resolution ◽  
Compressed Sensing ◽  
Dynamic Mri

WE-G-WAB-04: Ultra-Fast Dynamic MRI for Lung Tumor Tracking Based On Compressed Sensing and Low-Rank Decomposition in the Spatial-Temporal Domain

2013 ◽  
Vol 40 (6Part30) ◽  
pp. 506-506
Author(s):  
M Sarma ◽  
P Hu ◽  
D Ennis ◽  
A Thomas ◽  
P Lee ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Lung Tumor ◽  
Dynamic Mri ◽  
Low Rank ◽  
Tumor Tracking ◽  
Temporal Domain ◽  
Rank Decomposition ◽  
Low Rank Decomposition ◽  
Fast Dynamic

scholarly journals Jacobian weighted temporal total variation for motion compensated compressed sensing reconstruction of dynamic MRI

2016 ◽  
Vol 77 (3) ◽  
pp. 1208-1215 ◽  
Author(s):  
Javier Royuela-del-Val ◽  
Lucilio Cordero-Grande ◽  
Federico Simmross-Wattenberg ◽  
Marcos Martín-Fernández ◽  
Carlos Alberola-López
Keyword(s):  
Compressed Sensing ◽  
Total Variation ◽  
Dynamic Mri

Combination of compressed sensing and parallel imaging for highly-accelerated dynamic MRI

2012 ◽  
Author(s):  
Ricardo Otazo ◽  
Li Feng ◽  
Hersh Chandarana ◽  
Tobias Block ◽  
Leon Axel ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Parallel Imaging ◽  
Dynamic Mri

scholarly journals Compressed Sensing for fMRI: Feasibility Study on the Acceleration of Non-EPI fMRI at 9.4T

2015 ◽  
Vol 2015 ◽  
pp. 1-24 ◽  
Author(s):  
Paul Kyu Han ◽  
Sung-Hong Park ◽  
Seong-Gi Kim ◽  
Jong Chul Ye
Keyword(s):  
High Resolution ◽  
Compressed Sensing ◽  
Temporal Resolution ◽  
High Performance ◽  
Dynamic Mri ◽  
Local Magnetic Field ◽  
Planar Imaging ◽  
Somatosensory Stimulation ◽  
Echo Planar ◽  
Statistical Criteria

Conventional functional magnetic resonance imaging (fMRI) technique known as gradient-recalled echo (GRE) echo-planar imaging (EPI) is sensitive to image distortion and degradation caused by local magnetic field inhomogeneity at high magnetic fields. Non-EPI sequences such as spoiled gradient echo and balanced steady-state free precession (bSSFP) have been proposed as an alternative high-resolution fMRI technique; however, the temporal resolution of these sequences is lower than the typically used GRE-EPI fMRI. One potential approach to improve the temporal resolution is to use compressed sensing (CS). In this study, we tested the feasibility ofk-tFOCUSS—one of the high performance CS algorithms for dynamic MRI—for non-EPI fMRI at 9.4T using the model of rat somatosensory stimulation. To optimize the performance of CS reconstruction, different sampling patterns andk-tFOCUSS variations were investigated. Experimental results show that an optimizedk-tFOCUSS algorithm with acceleration by a factor of 4 works well for non-EPI fMRI at high field under various statistical criteria, which confirms that a combination of CS and a non-EPI sequence may be a good solution for high-resolution fMRI at high fields.

scholarly journals Deformation Corrected Compressed Sensing (DC-CS): A Novel Framework for Accelerated Dynamic MRI

2015 ◽  
Vol 34 (1) ◽  
pp. 72-85 ◽  
Author(s):  
Sajan Goud Lingala ◽  
Edward DiBella ◽  
Mathews Jacob
Keyword(s):  
Compressed Sensing ◽  
Dynamic Mri
Sign in / Sign up

Export Citation Format

Share Document