Title | ||
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Impatient Mri: Illinois Massively Parallel Acceleration Toolkit For Image Reconstruction With Enhanced Throughput In Mri |
Abstract | ||
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Much progress has been made in the design of efficient acquisition trajectories for high spatial and temporal resolution in magnetic resonance imaging (MRI). Additionally, significant developments in image reconstruction have enabled the reconstruction of reasonable images from massively undersampled or noisy data that is corrupted by a variety of physical effects, including magnetic field inhomogeneity. Translation of these techniques into clinical imaging has been impeded by the need for expertise and computational facilities to realize the potential of these methods. We present the Illinois Massively Parallel Acceleration Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI), a reconstruction utility that enables advanced techniques within clinically relevant computation times by using the computational power available in low-cost graphics processing cards. |
Year | DOI | Venue |
---|---|---|
2011 | 10.1109/ISBI.2011.5872356 | 2011 8TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO |
Keywords | Field | DocType |
magnetic resonance imaging, graphics processing cards, field inhomogeneity, image regularization | Kernel (linear algebra),Graphics,Iterative reconstruction,Computer vision,Massively parallel,Computer science,Artificial intelligence,Throughput,Graphics processing unit,Real-time MRI,Magnetic resonance imaging | Conference |
ISSN | Citations | PageRank |
1945-7928 | 7 | 0.71 |
References | Authors | |
6 | 9 |
Name | Order | Citations | PageRank |
---|---|---|---|
Xiaolong Wu | 1 | 128 | 18.86 |
Jiading Gai | 2 | 34 | 4.86 |
Fan Lam | 3 | 50 | 9.14 |
Maojing Fu | 4 | 20 | 3.51 |
Justin P. Haldar | 5 | 350 | 35.40 |
Yue Zhuo | 6 | 18 | 2.90 |
Zhi-Pei Liang | 7 | 522 | 64.94 |
Wen-mei W. Hwu | 8 | 4322 | 511.62 |
Brad Sutton | 9 | 199 | 27.18 |