Integration of the denoising, inpainting and local harmonic B(z) algorithm for MREIT imaging of intact animals.

Conductivity imaging based on the current-injection MRI technique has been developed in magnetic resonance electrical impedance tomography. Current injected through a pair of surface electrodes induces a magnetic flux density distribution inside an imaging object, which results in additional magnetic field inhomogeneity. We can extract phase changes related to the current injection and obtain an image of the induced magnetic flux density. Without rotating the object inside the bore, we can measure only one component B(z) of the magnetic flux density B = (B(x), B(y), B(z)). Based on a relation between the internal conductivity distribution and B(z) data subject to multiple current injections, one may reconstruct cross-sectional conductivity images. As the image reconstruction algorithm, we have been using the harmonic B(z) algorithm in numerous experimental studies. Performing conductivity imaging of intact animal and human subjects, we found technical difficulties that originated from the MR signal void phenomena in the local regions of bones, lungs and gas-filled tubular organs. Measured B(z) data inside such a problematic region contain an excessive amount of noise that deteriorates the conductivity image quality. In order to alleviate this technical problem, we applied hybrid methods incorporating ramp-preserving denoising, harmonic inpainting with isotropic diffusion and ROI imaging using the local harmonic B(z) algorithm. These methods allow us to produce conductivity images of intact animals with best achievable quality. We suggest guidelines to choose a hybrid method depending on the overall noise level and existence of distinct problematic regions of MR signal void.

[1]  Eung Je Woo,et al.  Magnetic resonance electrical impedance tomography (MREIT) for high-resolution conductivity imaging , 2008, Physiological measurement.

[2]  Harmonic decomposition in PDE-based denoising technique for magnetic resonance electrical impedance tomography , 2005, IEEE Transactions on Biomedical Engineering.

[3]  Bin He,et al.  Noninvasive Imaging of Bioimpedance Distribution by Means of Current Reconstruction Magnetic Resonance Electrical Impedance Tomography , 2008, IEEE Transactions on Biomedical Engineering.

[4]  Byung Il Lee,et al.  In vivo electrical conductivity imaging of a canine brain using a 3 T MREIT system , 2008, Physiological measurement.

[5]  R M Henkelman,et al.  Measurement of nonuniform current density by magnetic resonance. , 1991, IEEE transactions on medical imaging.

[6]  C Gabriel,et al.  The dielectric properties of biological tissues: I. Literature survey. , 1996, Physics in medicine and biology.

[7]  R. Henkelman,et al.  Sensitivity of magnetic-resonance current-density imaging , 1992 .

[8]  M. Joy,et al.  In vivo detection of applied electric currents by magnetic resonance imaging. , 1989, Magnetic resonance imaging.

[9]  E. Woo,et al.  Identification of current density distribution in electrically conducting subject with anisotropic conductivity distribution. , 2005, Physics in medicine and biology.

[10]  Eung Je Woo,et al.  Magnetic Resonance Electrical Impedance Tomography (MREIT) , 2011, SIAM Rev..

[12]  Eung Je Woo,et al.  MREIT conductivity imaging of the postmortem canine abdomen using CoReHA. , 2009, Physiological measurement.

[13]  Eung Je Woo,et al.  MREIT conductivity imaging of canine head using multi-echo pulse sequence , 2010 .

[14]  Byung Il Lee,et al.  Electrical conductivity images of biological tissue phantoms in MREIT. , 2005, Physiological measurement.

[15]  Byung Il Lee,et al.  Conductivity imaging with low level current injection using transversal J-substitution algorithm in MREIT. , 2007, Physics in medicine and biology.

[16]  Ohin Kwon,et al.  Reconstruction of conductivity and current density images using only one component of magnetic field measurements , 2003, IEEE Transactions on Biomedical Engineering.

[17]  Byung Il Lee,et al.  Analysis of recoverable current from one component of magnetic flux density in MREIT and MRCDI , 2007, Physics in medicine and biology.

[18]  Byung Il Lee,et al.  Conductivity imaging of canine brain using a 3 T MREIT system: postmortem experiments , 2007, Physiological measurement.

[19]  Eung Je Woo,et al.  CoReHA: conductivity reconstructor using harmonic algorithms for magnetic resonance electrical impedance tomography (MREIT) , 2009 .

[20]  Y. Birgül,et al.  Use of the Magnetic Field Generated by the Internal Distribution of Injected Currents for Electrical Impedance Tomography (MR-EIT) , 1998 .

[21]  Eung Je Woo,et al.  Impedance tomography using internal current density distribution measured by nuclear magnetic resonance , 1994, Optics & Photonics.

[22]  Byung Il Lee,et al.  Noise analysis in magnetic resonance electrical impedance tomography at 3 and 11 T field strengths. , 2005, Physiological measurement.

[23]  Sverre Grimnes,et al.  Bioimpedance and Bioelectricity Basics , 2000 .

[24]  Byung Il Lee,et al.  Conductivity and current density image reconstruction using harmonic Bz algorithm in magnetic resonance electrical impedance tomography. , 2003, Physics in medicine and biology.

[25]  Byung Il Lee,et al.  Conductivity image reconstruction from defective data in MREIT: numerical Simulation and animal experiment , 2006, IEEE Transactions on Medical Imaging.

[26]  Eung Je Woo,et al.  In Vivo High-ResolutionConductivity Imaging of the Human Leg Using MREIT: The First Human Experiment , 2009, IEEE Transactions on Medical Imaging.

[27]  Eung Je Woo,et al.  Local Harmonic $B_z$ Algorithm With Domain Decomposition in MREIT: Computer Simulation Study , 2008, IEEE Transactions on Medical Imaging.

[28]  Eung Je Woo,et al.  MREIT of Postmortem Swine Legs using Carbon-hydrogel Electrodes , 2008 .

[29]  Byung Il Lee,et al.  Measurement of induced magnetic flux density using injection current nonlinear encoding (ICNE) in MREIT. , 2007, Physiological measurement.

[30]  Ozlem Birgul,et al.  In vivo MRI electrical impedance tomography (MREIT) of tumors. , 2006, Technology in cancer research & treatment.

[31]  Eung Je Woo,et al.  Ramp-Preserving Denoising for Conductivity Image Reconstruction in Magnetic Resonance Electrical Impedance Tomography , 2011, IEEE Transactions on Biomedical Engineering.

[32]  Ohin Kwon,et al.  Magnetic resonance electrical impedance tomography at 3 tesla field strength , 2004, Magnetic resonance in medicine.

[33]  Byung Il Lee,et al.  Reconstruction of current density distributions in axially symmetric cylindrical sections using one component of magnetic flux density: computer simulation study. , 2003, Physiological measurement.

[34]  Lee Soo-Yeol,et al.  Improved Current Source Design to Measure Induced Magnetic Flux Density Distributions in MREIT , 2006 .

[35]  Ozlem Birgul,et al.  Measurement of ion diffusion using magnetic resonance electrical impedance tomography , 2006, Physics in medicine and biology.

[36]  Hyun Soo Nam,et al.  Optimization of multiply acquired magnetic flux density B(z) using ICNE-Multiecho train in MREIT. , 2010, Physics in medicine and biology.