TY - GEN
T1 - Sparse MRI reconstruction via multiscale L0-continuation
AU - Trzasko, Joshua
AU - Manduca, Armando
AU - Borisch, Eric
N1 - Copyright:
Copyright 2009 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - "Compressed Sensing" and related L1-minimization methods for reconstructing sparse magnetic resonance images (MRI) acquired at sub-Nyquist rates have shown great potential for dramatically reducing exam duration. Nonetheless, the nontriviality of numerical implementation and computational intensity of these reconstruction algorithms has thus far precluded their widespread use in clinical practice. In this work, we propose a novel MRI reconstruction framework based on homotopy continuation of the L 0 semi-norm using redescending M-estimator functions. Following analysis of the continuation scheme, the sparsity measure is extended to multiscale form and a simple numerical solver that can achieve accurate reconstructions in a matter of seconds on a standard desktop computer is presented.
AB - "Compressed Sensing" and related L1-minimization methods for reconstructing sparse magnetic resonance images (MRI) acquired at sub-Nyquist rates have shown great potential for dramatically reducing exam duration. Nonetheless, the nontriviality of numerical implementation and computational intensity of these reconstruction algorithms has thus far precluded their widespread use in clinical practice. In this work, we propose a novel MRI reconstruction framework based on homotopy continuation of the L 0 semi-norm using redescending M-estimator functions. Following analysis of the continuation scheme, the sparsity measure is extended to multiscale form and a simple numerical solver that can achieve accurate reconstructions in a matter of seconds on a standard desktop computer is presented.
KW - Homotopy
KW - L- minimization
KW - Magnetic resonance imaging
KW - Sparse reconstruction
UR - http://www.scopus.com/inward/record.url?scp=47849110073&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=47849110073&partnerID=8YFLogxK
U2 - 10.1109/SSP.2007.4301242
DO - 10.1109/SSP.2007.4301242
M3 - Conference contribution
AN - SCOPUS:47849110073
SN - 142441198X
SN - 9781424411986
T3 - IEEE Workshop on Statistical Signal Processing Proceedings
SP - 176
EP - 180
BT - 2007 IEEE/SP 14th Workshop on Statistical Signal Processing, SSP 2007, Proceedings
T2 - 2007 IEEE/SP 14th WorkShoP on Statistical Signal Processing, SSP 2007
Y2 - 26 August 2007 through 29 August 2007
ER -