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This book provides readers with an accessible and up-to-date introduction to the field of low-field MRI, which is currently seeing a resurgence in both research and commercial activity. It begins by presenting a historical overview of MRI system design and discussing current developments. It then analyzes the underlying physics of MRI from a semi-classical perspective before describing the major hardware components of low-field scanners (including the magnet, coils, transmitters, receivers, gradient systems, and digital processors) in detail. Several examples of each component are described to…mehr

Produktbeschreibung
This book provides readers with an accessible and up-to-date introduction to the field of low-field MRI, which is currently seeing a resurgence in both research and commercial activity. It begins by presenting a historical overview of MRI system design and discussing current developments. It then analyzes the underlying physics of MRI from a semi-classical perspective before describing the major hardware components of low-field scanners (including the magnet, coils, transmitters, receivers, gradient systems, and digital processors) in detail. Several examples of each component are described to solidify the reader's understanding of the major challenges and trade-offs involved in designing these complex devices. Finally, the issues involved in integrating these components within a working system are highlighted by presenting the architecture, design, and test results of two fully functional low-field MRI scanners that were designed and developed by the authors.
Autorenporträt
David J. Ariando received a Ph.D. from the Electrical and Computer Engineering Department at the University of Florida, Gainesville, FL with his doctoral degree in March 2023. His doctoral research was focused on developing electronics for Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) systems that can be used in portable applications. David was raised in Bandung, Indonesia, and obtained his M.S. degree from Case Western Reserve University, Cleveland, OH, in 2019. His current research interests include instrumentation for sensor physics, including NMR, MRI, and ultrasound. He has developed several generations of custom low-field NMR and MRI systems, including circuit simulations, design and implementation of high-speed analog, digital, and RF circuits, digital system design using FPGAs and microcontrollers for high-speed signal generation and acquisition, and post-acquisition signal processing (using MATLAB and Python). In his free time, he likes to play guitar, bass, drums, tennis, and chess, as well as enjoy nature. Soumyajit Mandal received the B.Tech. degree in electronics and electrical communications engineering from IIT Kharagpur, Kharagpur, India, in 2002, and the M.S. and Ph.D. degrees in electrical engineering from the Massachusetts Institute of Technology (MIT), Cambridge, MA, in 2004 and 2009, respectively. He was a Research Scientist with Schlumberger-Doll Research, Cambridge, MA (2010 to 2014), an Assistant Professor with the Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH (2014 to 2019), and an Associate Professor with the Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL (2020 to 2021). He is currently a member of the Research Staff in the Instrumentation Division at Brookhaven National Laboratory, Upton, NY. He has over 175 publications in peer-reviewed journals and conferences and has been awarded 26 patents. His research interests include low-power analog and RF circuits, embedded systems, magnetic resonance imaging and spectroscopy, and precision instrumentation for various biomedical and sensor interface applications. Dr. Mandal received the President of India Gold Medal in 2002, the MIT Microsystems Technology Laboratories (MTL) Doctoral Dissertation Award in 2009, the T. Keith Glennan Fellowship in 2016, and the IIT Kharagpur Young Alumni Achievers Award in 2018. He is a Senior Member of the IEEE.