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Selection of K‐space samples in localized MR spectroscopy of arbitrary volumes of interest
Author(s) -
Reeves Stanley J.
Publication year - 1995
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.1880050222
Subject(s) - k space , image (mathematics) , set (abstract data type) , selection (genetic algorithm) , space (punctuation) , computer science , image quality , quality (philosophy) , artificial intelligence , algorithm , mathematics , pattern recognition (psychology) , nuclear magnetic resonance , physics , mathematical analysis , fourier transform , quantum mechanics , programming language , operating system
A number of Image modeling techniques have been proposed to represent magnetic resonance spectro‐scopic images. The goal of these techniques is to reduce the amount of data and thus the time required to reconstruct the image. However, little attention has been given to the choice of k‐space samples. The combination of samples acquired has a great effect on the quality of the reconstructed image. A new method for optimizing the choice of k‐space samples—in which samples from a candidate set are sequentially eliminated in a computationally efficient manner until the desired number remain—is presented and demonstrated by means of simulations.