Title :
An investigation of an adaptive modeling algorithm for magnetic resonance image reconstruction
Author :
Yang, J. ; Smith, M. ; Nichols, S.T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada
Abstract :
For estimating the AR (autoregressive) parameters from nonstationary MR (magnetic resonance) data, the authors introduce an algorithm with an adaptive mechanism, which attempts to follow the statistical variation of the data. Medical and material MR images reconstructed using the LSL (least-squares lattice) algorithm were more stable than the original nonadaptive TERA (transient error reconstruction algorithm) ARMA (autoregressive moving average) modeling algorithm. Stability with that algorithm was obtained by using several ad-hoc methods which did not make best use of the available resolution achieved by using modeling. Stability with the LSL algorithm was obtained by its adaptive characteristics to allow it to follow the varying properties
Keywords :
adaptive signal processing; autoregressive moving average processes; biomedical NMR; image reconstruction; least squares approximations; parameter estimation; stability; adaptive modeling algorithm; autoregressive moving average; least-squares lattice; magnetic resonance image reconstruction; resolution; stability; statistical variation; transient error reconstruction algorithm; Autoregressive processes; Discrete Fourier transforms; Diseases; Error correction; Image reconstruction; Image resolution; Least squares methods; Magnetic resonance; Magnetic resonance imaging; Reconstruction algorithms;
Conference_Titel :
Communications, Computers and Signal Processing, 1993., IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-0971-5
DOI :
10.1109/PACRIM.1993.407293
