Table of Contents
ISRN Biomedical Imaging
Volume 2013, Article ID 826508, 9 pages
Research Article

Application of Linear Prediction for Phase and Magnitude Correction in Partially Acquired MRI

Medical Image Computing and Signal Processing Laboratory, Indian Institute of Information Technology and Management-Kerala (IIITM-K), Trivandrum 695 581, India

Received 31 August 2013; Accepted 25 September 2013

Academic Editors: B. Tomanek and G. Waiter

Copyright © 2013 Joseph Suresh Paul and Uma Krishna Swamy Pillai. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Using the boxcar representation in the spatial domain and a signal-space representation of its frequency-weighted -space, an iterative prediction method is developed to derive an improved low-resolution phase approximation for phase correction. Compared to the homodyne filter, the proposed predictor is found to be more efficient due to its capability of exhibiting an equivalent degree of performance using a lower number of fractional lines. The phase correction performance is illustrated using partially acquired susceptibility weighted images (SWI). An extension of the predictor into higher frequency regions of phase-encodes in conjunction with a signal-space projection in the frequency-weighted partial k-space is shown to provide restoration of fine structural details of sparse magnitude images. The application of subspace projection filtering is demonstrated using magnetic resonance angiogram (MRA).