Magnetic Resonance Image Reconstruction: Theory, Methods, and Applications (Volume 7) (Advances in Magnetic Resonance Technology and Applications, Volume 7) - Softcover

 
9780128227268: Magnetic Resonance Image Reconstruction: Theory, Methods, and Applications (Volume 7) (Advances in Magnetic Resonance Technology and Applications, Volume 7)

Synopsis

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

"synopsis" may belong to another edition of this title.

About the Authors

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.

Dr Claudia Prieto is a Reader in the School of Biomedical Engineering & Imaging Sciences

From the Back Cover

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. It discusses approaches for specific applications such as non-Cartesian imaging, under sampled reconstruction, motion correction, dynamic imaging and quantitative MRI.

The reader will be able to:

  • Describe magnetic resonance image reconstruction as an inverse problem
  • Recognize advantages and disadvantages of several objective functions, practical algorithms and system models used for magnetic resonance image reconstruction
  • Implement basic techniques for magnetic resonance image reconstruction
  • Identify reconstruction methods for specific applications of magnetic resonance imaging

Magnetic Resonance Image Reconstruction: Theory, Methods and Applications is a unique resource suitable for physicists, engineers, technologists and clinicians with an interest in medical image reconstruction and MRI

"About this title" may belong to another edition of this title.