Denoising of B₁⁺ field maps for noise-robust image reconstruction in electrical properties tomography.

PURPOSE To validate the use of adaptive nonlinear filters in reconstructing conductivity and permittivity images from the noisy B₁(+) maps in electrical properties tomography (EPT). METHODS In EPT, electrical property images are computed by taking Laplacian of the B₁(+) maps. To mitigate the noise amplification in computing the Laplacian, the authors applied adaptive nonlinear denoising filters to the measured complex B₁(+) maps. After the denoising process, they computed the Laplacian by central differences. They performed EPT experiments on phantoms and a human brain at 3 T along with corresponding EPT simulations on finite-difference time-domain models. They evaluated the EPT images comparing them with the ones obtained by previous EPT reconstruction methods. RESULTS In both the EPT simulations and experiments, the nonlinear filtering greatly improved the EPT image quality when evaluated in terms of the mean and standard deviation of the electrical property values at the regions of interest. The proposed method also improved the overall similarity between the reconstructed conductivity images and the true shapes of the conductivity distribution. CONCLUSIONS The nonlinear denoising enabled us to obtain better-quality EPT images of the phantoms and the human brain at 3 T.

[1]  Olaf Dössel,et al.  Determination of Electric Conductivity and Local SAR Via B1 Mapping , 2009, IEEE Transactions on Medical Imaging.

[2]  D. Hoult The principle of reciprocity in signal strength calculations—a mathematical guide , 2000 .

[3]  Min Hyoung Cho,et al.  Geometric nonlinear diffusion filter and its application to X-ray imaging , 2011, Biomedical engineering online.

[4]  Peter R Luijten,et al.  B  1+ Phase mapping at 7 T and its application for in vivo electrical conductivity mapping , 2012, Magnetic resonance in medicine.

[5]  R. W. Lau,et al.  The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz to 20 GHz. , 1996, Physics in medicine and biology.

[6]  Glen R Morrell,et al.  A phase‐sensitive method of flip angle mapping , 2008, Magnetic resonance in medicine.

[7]  Vasily L Yarnykh,et al.  Actual flip‐angle imaging in the pulsed steady state: A method for rapid three‐dimensional mapping of the transmitted radiofrequency field , 2007, Magnetic resonance in medicine.

[8]  D. Yeo,et al.  Conductivity and permittivity imaging at 3.0T. , 2012, Concepts in magnetic resonance. Part B, Magnetic resonance engineering.

[9]  Niels Kuster,et al.  The Virtual Family—development of surface-based anatomical models of two adults and two children for dosimetric simulations , 2010, Physics in medicine and biology.

[10]  Tobias Voigt,et al.  Quantitative conductivity and permittivity imaging of the human brain using electric properties tomography , 2011, Magnetic resonance in medicine.

[11]  C. Ahn,et al.  A New Phase Correction Method in NMR Imaging Based on Autocorrelation and Histogram Analysis , 1987, IEEE Transactions on Medical Imaging.

[12]  R. W. Lau,et al.  The dielectric properties of biological tissues: III. Parametric models for the dielectric spectrum of tissues. , 1996, Physics in medicine and biology.

[13]  L. H. Kang,et al.  Fast B1 mapping based on interleaved-three-flip-angle (ITFA) excitation. , 2013, Medical physics.

[14]  Han Wen,et al.  Noninvasive quantitative mapping of conductivity and dielectric distributions using RF wave propagation effects in high-field MRI , 2003, SPIE Medical Imaging.

[15]  Kay Nehrke,et al.  In vivo determination of electric conductivity and permittivity using a standard MR system , 2007 .

[16]  Max A. Viergever,et al.  Efficient and reliable schemes for nonlinear diffusion filtering , 1998, IEEE Trans. Image Process..

[17]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Tobias Voigt,et al.  Electrical Properties Tomography in the Human Brain at 1.5, 3, and 7T: A Comparison Study , 2014, Magnetic resonance in medicine.

[19]  Guillermo Sapiro,et al.  Robust anisotropic diffusion , 1998, IEEE Trans. Image Process..

[20]  E M Haacke,et al.  Extraction of conductivity and permittivity using magnetic resonance imaging , 1991 .

[21]  P Wach,et al.  Imaging of the active B1 field in vivo , 1996, Magnetic resonance in medicine.

[22]  C. Werner,et al.  Satellite radar interferometry: Two-dimensional phase unwrapping , 1988 .

[23]  Bin He,et al.  Imaging Electric Properties of Biological Tissues by RF Field Mapping in MRI , 2010, IEEE Transactions on Medical Imaging.

[24]  F. Wiesinger,et al.  B1 mapping by Bloch‐Siegert shift , 2010, Magnetic resonance in medicine.

[25]  O. Doessel,et al.  Patient‐individual local SAR determination: In vivo measurements and numerical validation , 2012, Magnetic resonance in medicine.

[26]  Peter Börnert,et al.  DREAM—a novel approach for robust, ultrafast, multislice B1 mapping , 2012, Magnetic resonance in medicine.

[27]  K. Kuroda,et al.  An inverse method to optimize heating conditions in RF-capacitive hyperthermia , 1996, IEEE Transactions on Biomedical Engineering.

[28]  U Klose,et al.  Fast 3D radiofrequency field mapping using echo‐planar imaging , 2006, Magnetic resonance in medicine.

[29]  S R Arridge,et al.  Direct calculation of the moments of the distribution of photon time of flight in tissue with a finite-element method. , 1995, Applied optics.