31. Complex Thresholding Methods for Eliminating Voxels That Contain Predominantly Noise in Magnetic Resonance Images
- E. Mark Haacke3,4,5,6,7,
- Jürgen R. Reichenbach8,9
Published Online: 18 JAN 2011
DOI: 10.1002/9780470905203.ch31
Copyright © 2011 Wiley-Blackwell
Book Title

Susceptibility Weighted Imaging in MRI: Basic Concepts and Clinical Applications
Additional Information
How to Cite
Rowe, D. B., Jiang, J. and Haacke, E. M. (2011) Complex Thresholding Methods for Eliminating Voxels That Contain Predominantly Noise in Magnetic Resonance Images, in Susceptibility Weighted Imaging in MRI: Basic Concepts and Clinical Applications (eds E. M. Haacke and J. R. Reichenbach), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470905203.ch31
Editor Information
- 3
Department of Radiology, Wayne State University, Detroit, MI, USA
- 4
The MRI Institute for Biomedical Research, Detroit, MI, USA
- 5
Department of Physics, Case Western Reserve University, Cleveland, OH, USA
- 6
Department of Radiology, Loma Linda University, Loma Linda, CA, USA
- 7
School of Biomedical Engineering and Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
- 8
Medical Physics Group, Department of Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany
- 9
Medical Physics Group, Department of Diagnostic and Interventional Radiology, Friedrich Schiller University, Jena, Germany
Publication History
- Published Online: 18 JAN 2011
- Published Print: 24 JAN 2011
ISBN Information
Print ISBN: 9780470043431
Online ISBN: 9780470905203
- Summary
- Chapter
- References
Keywords:
- complex thresholding methods, voxel elimination - noise removal in magnetic resonance images, improving phase image visualization;
- MAPHT method, local statistic - measured signal at voxel of interest and its neighbors, defined;
- magnitude and phase thresholding method, MAPHT method - for simulated and human MRI data, and human brain SWI data
Summary
This chapter contains sections titled:
Introduction
The CTM Method
Connectivity
Simulated Data
Human Data
Concluding Remarks
References
