TY - JOUR
T1 - Compressed-sensing MRI with random encoding
AU - Haldar, Justin P.
AU - Hernando, Diego
AU - Liang, Zhi Pei
N1 - Funding Information:
Manuscript received August 10, 2010; revised September 16, 2010; accepted September 30, 2010. Date of publication October 11, 2010; date of current version April 01, 2011. This work was supported in part by the National Institutes of Health (NIH) under Grant NIH-P41-EB001977-21 and Grant NIH-P41-RR023953-01, and in part by the National Science Foundation (NSF) NSF-CBET-07-30623. Asterisk indicates corresponding author. *J. Haldar is with the Department of Electrical and Computer Engineering and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801 USA.
PY - 2011/4
Y1 - 2011/4
N2 - Compressed sensing (CS) has the potential to reduce magnetic resonance (MR) data acquisition time. In order for CS-based imaging schemes to be effective, the signal of interest should be sparse or compressible in a known representation, and the measurement scheme should have good mathematical properties with respect to this representation. While MR images are often compressible, the second requirement is often only weakly satisfied with respect to commonly used Fourier encoding schemes. This paper investigates the use of random encoding for CS-MRI, in an effort to emulate the universal encoding schemes suggested by the theoretical CS literature. This random encoding is achieved experimentally with tailored spatially-selective radio-frequency (RF) pulses. Both simulation and experimental studies were conducted to investigate the imaging properties of this new scheme with respect to Fourier schemes. Results indicate that random encoding has the potential to outperform conventional encoding in certain scenarios. However, our study also indicates that random encoding fails to satisfy theoretical sufficient conditions for stable and accurate CS reconstruction in many scenarios of interest. Therefore, there is still no general theoretical performance guarantee for CS-MRI, with or without random encoding, and CS-based methods should be developed and validated carefully in the context of specific applications.
AB - Compressed sensing (CS) has the potential to reduce magnetic resonance (MR) data acquisition time. In order for CS-based imaging schemes to be effective, the signal of interest should be sparse or compressible in a known representation, and the measurement scheme should have good mathematical properties with respect to this representation. While MR images are often compressible, the second requirement is often only weakly satisfied with respect to commonly used Fourier encoding schemes. This paper investigates the use of random encoding for CS-MRI, in an effort to emulate the universal encoding schemes suggested by the theoretical CS literature. This random encoding is achieved experimentally with tailored spatially-selective radio-frequency (RF) pulses. Both simulation and experimental studies were conducted to investigate the imaging properties of this new scheme with respect to Fourier schemes. Results indicate that random encoding has the potential to outperform conventional encoding in certain scenarios. However, our study also indicates that random encoding fails to satisfy theoretical sufficient conditions for stable and accurate CS reconstruction in many scenarios of interest. Therefore, there is still no general theoretical performance guarantee for CS-MRI, with or without random encoding, and CS-based methods should be developed and validated carefully in the context of specific applications.
KW - Compressed sensing
KW - magnetic resonance imaging (MRI)
KW - radio-frequency encoding
UR - http://www.scopus.com/inward/record.url?scp=79953740726&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79953740726&partnerID=8YFLogxK
U2 - 10.1109/TMI.2010.2085084
DO - 10.1109/TMI.2010.2085084
M3 - Article
C2 - 20937579
AN - SCOPUS:79953740726
VL - 30
SP - 893
EP - 903
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
SN - 0278-0062
IS - 4
M1 - 5599301
ER -