In Magnetic Resonance Electrical Impedance Tomography (MREIT), we measure the induced magnetic flux density inside an imaging object subject to an external injection current. The magnetic flux density is contaminated with noise and this ultimately limits the quality of reconstructed conductivity and current density images. By using two methods to analyze amounts of noise in 3T and 11T MREIT systems, we found that a carefully designed MREIT study will be able to reduce the noise level below 0.1 nT.
We present cross-sectional conductivity images of a biological tissue phantom obtained by using a 3.0 Tesla magnetic resonance electrical impedance tomography (MREIT) system. Inside the cylindrical phantom with 140 mm diameter and 140 mm height, biological tissues such as bovine tongue and liver, porcine muscle, and chicken breast were placed within an agar gelatin. Injecting current of 480 mA.ms into the tissue phantom, we measured the z-component B/sub z/ of the induced magnetic flux density B=(B/sub x/, B/sub y/, B/sub z/). Using the harmonic B/sub z/ algorithm, we reconstructed cross-sectional conductivity images from the measured B/sub z/ data. Reconstructed images clearly distinguish different tissues in terms of both their shapes and conductivity values.
Recent progress in magnetic resonance electrical impedance tomography (MREIT) research has shown that conductivity images with higher spatial resolution and accuracy are achievable. One of the most important remaining problems to be solved in MREIT before we can apply the technique to human subjects is how to reduce the amount of injection current. Since we use an MRI scanner to measure the induced magnetic flux density data subject to an injection current, the data is contaminated with random noise. In order to obtain enough signal-to-noise ratio (SNR), we need to inject a large amount of current into the subject. However, it is obvious that we must comply with the electrical safety regulations and this means that we should deal with noisy data having a low SNR due to the limited amount of injection current. Furthermore, in the developed reconstruction algorithms, the required numerical differentiations of the noisy data may result in deterioration of the reconstructed conductivity image leading to a loss of important information. We propose a PDE-based denoising technique that diminishes the degradation of reconstructed conductivity images due to the noise in measured data. The proposed PDE-based technique is advantageous in reducing the random noise while preserving useful features in MREIT.
Magnetic resonance electrical impedance tomography (MREIT) has been developed as a new medical imaging modality providing high-resolution conductivity and current density images. This paper is about MREIT of the breast. To show the feasibility of breast MREIT, we carried numerical simulations and breast phantom experiments. We found that an anomaly with 4 mm diameter can be visualized in a reconstructed conductivity image using 5 mA injection current if the SNR of the corresponding MR magnitude image is at least 150. We propose a desirable electrode configuration and show our first experimental results of the breast MREIT. Developing an RF coil for the breast MREIT, we plan to conduct various experimental studies including tissue phantoms.
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