DocumentCode :
1508171
Title :
Guest Editorial Compressive Sensing for Biomedical Imaging
Author :
Ge Wang ; Bresler, Yoram ; Ntziachristos, Vasilis
Author_Institution :
VT-WFU Sch. of Biomed. Eng. & Sci., Virginia Tech, Blacksburg, VA, USA
Volume :
30
Issue :
5
fYear :
2011
fDate :
5/1/2011 12:00:00 AM
Firstpage :
1013
Lastpage :
1016
Abstract :
Compressive sensing (CS) has seen impressive successes and fast growth over the past ten years, including applications in medical imaging. Applications of CS to magnetic resonance imaging (MRI) have been the earliest, most numerous, and most diverse, owing to the tremendous flexibility in designing the acquisition process and the pressing need that MRI has, as a slow acquisition modality, to reduce the sampling requirements.
Keywords :
biomedical MRI; data compression; image coding; medical image processing; L1-norm minimization; biomedical imaging; compressive sensing; data acquisition process; greedy algorithms; image compression; optimization procedure; uncompressed image; Compressed sensing; Special issues and sections;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2011.2145070
Filename :
5760046
Link To Document :
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