Literature DB >> 19553050

MAgnitude and PHase Thresholding (MAPHT) of noisy complex-valued magnetic resonance images.

Daniel B Rowe1, E Mark Haacke.   

Abstract

It is often desirable to separate voxels that contain signal from tissue along with measurement noise from those that contain purely measurement noise. Generally, this separation called thresholding utilizes only the magnitude portion of the images. Recently, methods have been developed that utilize both the magnitude and phase for thresholding voxels. This manuscript is an extension previous work and uses the bivariate normality of the real and imaginary values with phase coupled means. A likelihood ratio statistic is derived that simplifies to a more familiar form that is F-distributed in large samples. It is shown that in small samples, critical values from Monte Carlo simulation can be used to threshold this statistic with the proper Type I and Type II error rates. This method is applied to susceptibility weighted magnetic resonance images and shown to produce increased tissue contrast.

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Year:  2009        PMID: 19553050      PMCID: PMC2763057          DOI: 10.1016/j.mri.2009.05.008

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  8 in total

1.  Susceptibility weighted imaging (SWI).

Authors:  E Mark Haacke; Yingbiao Xu; Yu-Chung N Cheng; Jürgen R Reichenbach
Journal:  Magn Reson Med       Date:  2004-09       Impact factor: 4.668

2.  An evaluation of thresholding techniques in fMRI analysis.

Authors:  Brent R Logan; Daniel B Rowe
Journal:  Neuroimage       Date:  2004-05       Impact factor: 6.556

3.  Signal and noise of Fourier reconstructed fMRI data.

Authors:  Daniel B Rowe; Andrew S Nencka; Raymond G Hoffmann
Journal:  J Neurosci Methods       Date:  2006-09-01       Impact factor: 2.390

4.  An evaluation of spatial thresholding techniques in fMRI analysis.

Authors:  Brent R Logan; Maya P Geliazkova; Daniel B Rowe
Journal:  Hum Brain Mapp       Date:  2008-12       Impact factor: 5.038

5.  Complex threshold method for identifying pixels that contain predominantly noise in magnetic resonance images.

Authors:  Daniel S J Pandian; Carlo Ciulla; E Mark Haacke; Jing Jiang; Muhammad Ayaz
Journal:  J Magn Reson Imaging       Date:  2008-09       Impact factor: 4.813

6.  Noise in MRI.

Authors:  A Macovski
Journal:  Magn Reson Med       Date:  1996-09       Impact factor: 4.668

7.  Improved detectability in low signal-to-noise ratio magnetic resonance images by means of a phase-corrected real reconstruction.

Authors:  M A Bernstein; D M Thomasson; W H Perman
Journal:  Med Phys       Date:  1989 Sep-Oct       Impact factor: 4.071

8.  Measurement of signal intensities in the presence of noise in MR images.

Authors:  R M Henkelman
Journal:  Med Phys       Date:  1985 Mar-Apr       Impact factor: 4.071

  8 in total
  1 in total

1.  Complex and magnitude-only preprocessing of 2D and 3D BOLD fMRI data at 7 T.

Authors:  Robert L Barry; Stephen C Strother; John C Gore
Journal:  Magn Reson Med       Date:  2011-07-11       Impact factor: 4.668

  1 in total

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