MRI Physics, Image Reconstruction, and Analysis

The field of magnetic resonance imaging (MRI) has developed rapidly over the past decade, benefiting greatly from the newly developed framework of compressed sensing and its ability to drastically reduce MRI scan times. MRI: Physics, Image Reconstruction, and Analysis presents the latest research in MRI technology, emphasizing compressed sensing-based image reconstruction techniques. The book begins with a succinct introduction to the principles of MRI and then: Discusses the technology and applications of T1rho MRI Details the recovery of highly sampled functional MRIs Explains sparsity-based techniques for quantitative MRIs Describes multi-coil parallel MRI reconstruction techniques Examines off-line techniques in dynamic MRI reconstruction Explores advances in brain connectivity analysis using diffusion and functional MRIs Featuring chapters authored by field experts, MRI: Physics, Image Reconstruction, and Analysis delivers an authoritative and cutting-edge treatment of MRI reconstruction techniques. The book provides engineers, physicists, and graduate students with a comprehensive look at the state of the art of MRI.

T1rho MR Imaging: Principle, Technology, and ApplicationJing Yuan and Yi-Xiang J. Wang Recursive Reconstruction of Highly Undersampled Functional MRI SequencesWei Lu, Ian C. Atkinson, and Namrata Vaswani Compressed Sensing in Quantitative MRIsMariya Doneva and Alfred Mertins Parallel Magnetic Resonance ImagingMartin Uecker Parallel Imaging and ReconstructionSreenath Narayan and Jun Miao Accelerated Dynamic MRI Using Adaptive Signal ModelsSajan Goud Lingala and Mathews Jacob Brain Connectivity Mapping and Analysis Using Diffusion MRIBrian G. Booth and Ghassan Hamarneh Brain Connectivity Assessed with Functional MRIAiping Liu, Junning Li, Martin J. McKeown, and Z. Jane Wang

Angshul Majumdar is an assistant professor of electronics and communications engineering at the Indraprastha Institute of Information Technology, Delhi, India. He received his Ph.D from the University of British Columbia, Vancouver, Canada. Dr. Majumdar has published more than 50 papers in top-tier journals and conferences during the past 5 years, including more than 25 papers on reducing the acquisition time in magnetic resonance imaging and several papers on robust classification techniques with applications in face recognition, fingerprint recognition, and optical character recognition. Before he started in academia, he worked as a business consultant for PricewaterhouseCoopers. Rabab Ward is a professor in the Electrical and Computer Engineering Department at the University of British Columbia, Vancouver, Canada. She has published more than 150 refereed journal papers and 300 refereed conference articles, and holds 6 patents. A fellow of several professional societies, Dr. Ward is highly decorated, having received the highest award of the IEEE Signal Processing Society; the Association of Professional Engineers and Geoscientists of British Columbia’s top engineering award; and more. She is currently president-elect of the IEEE Signal Processing Society. She was the general chair of IEEE ICIP 2000 and co-chair of IEEE ICASSP 2013.