Magnetic Resonance Image Reconstruction : Theory, Methods, and Applications

Magnetic Resonance Image Reconstruction: Theory, Methods and Applications presents the fundamental concepts of MR image reconstruction, including its formulation as an inverse problem, as well as the most common models and optimization methods for reconstructing MR images. The book discusses approaches for specific applications such as non-Cartesian imaging, under sampled reconstruction, motion correction, dynamic imaging and quantitative MRI. This unique resource is suitable for physicists, engineers, technologists and clinicians with an interest in medical image reconstruction and MRI.

• Explains the underlying principles of MRI reconstruction, along with the latest research<
• Gives example codes for some of the methods presented
• Includes updates on the latest developments, including compressed sensing, tensor-based reconstruction and machine learning based reconstruction

Mehmet Akçakaya was born in Istanbul, Turkey. He went to Robert College for high school, moved to Montreal for undergraduate studies at McGill University, where he graduated with great distinction and Charles Michael Morssen Gold Medal. He got his PhD degree in May 2010 under the supervision of Professor Vahid Tarokh in the School of Engineering and Applied Sciences (SEAS), Harvard University.He was a post-doctoral fellow at BIDMC CMR Center between 2010-12, and an Instructor in Medicine at Harvard Medical School between 2012-15.

Mariya Doneva is a senior scientist at Philips Research, Hamburg, Germany. She received her BSc and MSc degrees in Physics from the University of Oldenburg in 2006 and 2007, respectively and her PhD degree in Physics from the University of Luebeck in 2010. She was a Research Associate at Electrical Engineering and Computer Sciences department at UC Berkeley between 2015 and 2016. She is a recipient of the Junior Fellow award of the International Society for Magnetic Resonance in Medicine. Her research interests include methods for efficient data acquisition, image reconstruction and quantitative parameter mapping in the context of magnetic resonance imaging.

Claudia Prieto, PhD, is a Professor at the Faculty of Engineering at the Pontificia Universidad Católica de Chile. She is an internationally recognized expert in cardiac magnetic resonance imaging (MRI), with more than 15 years of experience in MRI research. Her work focuses on developing and evaluating novel MRI techniques for improved assessment of cardiovascular disease, including acquisition, reconstruction, motion estimation and correction, quantitative MRI, and AI–based solutions for different stages of the imaging pipeline.