Experimental studies for LFEIT with magnetic field measurements

2018
Tetik, Ahmet Önder
Lorentz Force Electrical Impedance Tomography based on magnetic field measurements (LFEIT) is a hybrid imaging modality to image the electrical impedance of body tissues. In this modality, ultrasound pressure waves applied to the body tissues under static magnetic fields induce Lorentz currents. Magnetic flux density due to these currents is measured using receiver coils. The main aim of this thesis is to develop an experimental setup and a data acquisition system to obtain LFEIT sig nals from phantoms. Moreover, conductivity contrast images are formed using the measured LFEIT signals. For the data acquisition system, custom made contactless receiver coils in Helmholtz configuration are utilized and a two-stage cascaded amplifier is designed to obtain LFEIT signals. A magnetic field generator is built with permanent magnets to apply 0.56 T static magnetic field to phantoms in the experimental setup. In addition, 16-element Linear Phased Array (LPA) Transducer is used to steer ultrasound waves in the phantoms. Two different phantoms are prepared for experiments. In the first experiment, a conductive inhomogenity with 3 S/m conductivity is detected at 92 mm from the transducer surface. The last experiment is conducted with a phantom including sunflower oil and agar-gel having a cavity filled with 58 S/m solution. The transducer steers ultrasound waves from -20◦ to 20◦ with 1◦ step angle in the phantom. At each angle, data acquisition system records LFEIT signals. With this system, 58 S/m cavity with 15.15 mm height, 30 mm width and 20 mm length dimensions is detected at a depth of 75 mm. As a result, conductivity contrast image of this phantom is formed using LFEIT signals. 3 S/m is the lowest conductivity detected by this technique compared to the previous studies reported in the literature.

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Citation Formats
A. Ö. Tetik, “Experimental studies for LFEIT with magnetic field measurements,” M.S. - Master of Science, Middle East Technical University, 2018.