2014
DOI: 10.1109/tbme.2014.2304494
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A Reconstruction Algorithm of Magnetoacoustic Tomography With Magnetic Induction for an Acoustically Inhomogeneous Tissue

Abstract: Magnetoacoustic tomography with Magnetic Induction (MAT-MI) is a noninvasive electrical conductivity imaging approach that measures ultrasound wave induced by magnetic stimulation, for reconstructing the distribution of electrical impedance in biological tissue. Existing reconstruction algorithms for MAT-MI are based on the assumption that the acoustic properties in the tissue are homogeneous. However, the tissue in most parts of human body, has heterogeneous acoustic properties, which leads to potential disto… Show more

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Cited by 19 publications
(3 citation statements)
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“…Acoustic reflections due to the acoustic impedance heterogeneity will also create extra “noisy” acoustic sources that are not related to the electrical properties of the imaging objects and may provide extra information of the mechanical properties if modeled correctly in the future. Some recent studies have started to tackle this problem, and initial theoretical and computer simulation studies have demonstrated the feasibility to better quantify electrical conductivity in MAT-MI by mapping the inhomogeneous acoustic speed from ultrasound transmission tomography (Zhou et al , 2014). In addition, MAT-MI image reconstruction algorithms that can take into account the conductivity anisotropy need to be developed in the future, as electrical conductivity anisotropy in certain tissue types such as muscles and neural fibers has been suggested to change the MAT-MI signal significantly (Brinker and Roth, 2008; Li et al , 2013).…”
Section: Challenges and Future Directionsmentioning
confidence: 99%
See 1 more Smart Citation
“…Acoustic reflections due to the acoustic impedance heterogeneity will also create extra “noisy” acoustic sources that are not related to the electrical properties of the imaging objects and may provide extra information of the mechanical properties if modeled correctly in the future. Some recent studies have started to tackle this problem, and initial theoretical and computer simulation studies have demonstrated the feasibility to better quantify electrical conductivity in MAT-MI by mapping the inhomogeneous acoustic speed from ultrasound transmission tomography (Zhou et al , 2014). In addition, MAT-MI image reconstruction algorithms that can take into account the conductivity anisotropy need to be developed in the future, as electrical conductivity anisotropy in certain tissue types such as muscles and neural fibers has been suggested to change the MAT-MI signal significantly (Brinker and Roth, 2008; Li et al , 2013).…”
Section: Challenges and Future Directionsmentioning
confidence: 99%
“…Though demonstrated in computer simulation, such simplified approaches can hardly be applied on experimentally collected MAT-MI signal, which is dominated by conductivity gradient sources. As mentioned in some later theoretical studies (Kunyansky 2012, Zhou et al 2014, if it is possible to rotate the static magnetic field B 0 , e.g. setting it to three orthogonal directions, while keeping the magnetically induced eddy current in the conductive tissue sample the same, one may be able to get a good estimation of the curl of the eddy current ∇ × J and further estimate the electrical conductivity.…”
Section: Mapping Conductivity Through Mapping Mat-mi Acoustic Sourcementioning
confidence: 99%
“…Also, as compared to traditional ultrasound imaging, the MAT method has lower ultrasound attenuation due to the tissue from the reduced travel path of the acoustic waves from the MNPs embedded in tissue to the sensing transducer leading to improved imaging depth. The MAT method is similar to magneto acoustic tomography with magnetic induction (MAT-MI), which is being explored for high resolution bioimpedance imaging [7][33][34]. With MAT-MI a combination of pulsed and static magnetic fields are used to generate acoustic fields by using Lorentz force; this acoustic field can be used to estimate the high resolution conductivity distribution of the tissue.…”
Section: Introductionmentioning
confidence: 99%