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Portable and Autonomous Magnetic Resonance

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2020, Doctor of Philosophy, Case Western Reserve University, EECS - Electrical Engineering.
Nuclear magnetic resonance (NMR) is a powerful spectroscopic technique that has seen heavy use in the fields of physics and chemistry for studying physical and molecular compositions of liquid samples. Advancements in such technologies has led to the invention of magnetic resonance imaging (MRI) which is widely used in medical imaging due to its ability to create contrast in soft tissues. Beyond the applications above, magnetic resonance has also been applied to the investigation of porous media, quality control for food products, inspection of polymers, and the study of agricultural products. Despite the many potential applications, magnetic resonance (MR) techniques are often reserved for the academic/industrial laboratory or hospital. This can largely be attributed to the fact that MR systems generally utilize large superconducting magnets or complicated permanent magnet geometries to generate strong and uniform magnetic fields. As a result, MR systems are generally very expensive (in the range of \$800k - \$5 million for the scanner and \$3.25 to \$15 per liter of liquid helium), large, and the data acquisition methods are very complex. These factors contribute to the under-utilization of MR in industry. This dissertation addresses the problems described above by developing novel portable and autonomous MR systems. We develop MR systems that are based off of an FPGA SoC as well as an NMR ASIC chip as well as a TI micro-controller. Both systems allow for fully autonomous operation without the use of an external computer, enabling "edge" operation. We provide a brief comparison of each system and the pros and cons of each. We then discuss a low-cost, bench-top, NMR/MRI system coupled with a miniaturized gradient driver circuit. This system is used in the dissertation for bi-modal imaging experiments and autonomously classifying food products. Full automation of both data acquisition, data processing, and decision making is key to making MR a more widely used technique. We conclude the dissertation by discussing the development of a hand-held MRI sensor. Combining the systems and methods described above with a hand-held sensor can truly help to enable MRI as a widespread tool outside of the hospital.
Soumyajit Mandal (Advisor)
Christian Zorman (Committee Member)
Mark Griswold (Committee Member)
Robert Brown (Committee Member)
Yiqiao Tang (Committee Member)
217 p.

Recommended Citations

Citations

  • Greer, M. (2020). Portable and Autonomous Magnetic Resonance [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1586359944642158

    APA Style (7th edition)

  • Greer, Mason. Portable and Autonomous Magnetic Resonance. 2020. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1586359944642158.

    MLA Style (8th edition)

  • Greer, Mason. "Portable and Autonomous Magnetic Resonance." Doctoral dissertation, Case Western Reserve University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1586359944642158

    Chicago Manual of Style (17th edition)