Beyond the g-factor limit in sensitivity encoding using joint histogram entropy.
MAGN RESON MED
153 - 160.
The maximum practical speed-up that can be achieved using parallel imaging methods is widely accepted to be limited by g-factor noise. An approximate expression for the g-factor noise as a function of the principal eigenvector of the inverse sensitivity matrix is derived. This formulation allows g-factor enhanced noise to be reduced by a constrained optimization procedure with joint image histogram entropy between a reference image and a SENSE image as an image quality metric. The reference image does not need to have identical resolution or contrast. The reference image may also be used for coil calibration. The limits of the method are explored using simulated and real array coil data with high g-factor using a variety of contrast and resolution combinations. The method preserves image structure, contrast, and lesions even when these were not observable in the reference data. In all cases g-factor was dramatically reduced.
|Title:||Beyond the g-factor limit in sensitivity encoding using joint histogram entropy|
|Keywords:||SENSE, parallel imaging, g-factor, entropy, noise reduction, RECONSTRUCTION, REGISTRATION, IMAGES|
|UCL classification:||UCL > School of Life and Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > School of Life and Medical Sciences > Faculty of Medical Sciences > Medicine (Division of)
UCL > School of Life and Medical Sciences > Faculty of Medical Sciences > Medicine (Division of) > Metabolism and Experimental Therapeutics
UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Medical Physics and Bioengineering
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