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Magnetic Resonance Image Reconstruction

Magnetic Resonance Image Reconstruction PDF Author: Mehmet Akcakaya
Publisher: Academic Press
ISBN: 012822746X
Category : Science
Languages : en
Pages : 518

Book Description
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

Magnetic Resonance Image Reconstruction

Magnetic Resonance Image Reconstruction PDF Author: Mehmet Akcakaya
Publisher: Academic Press
ISBN: 012822746X
Category : Science
Languages : en
Pages : 518

Book Description
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

Principles of Magnetic Resonance Imaging

Principles of Magnetic Resonance Imaging PDF Author: Zhi-Pei Liang
Publisher: Wiley-IEEE Press
ISBN:
Category : Medical
Languages : en
Pages : 442

Book Description
In 1971 Dr. Paul C. Lauterbur pioneered spatial information encoding principles that made image formation possible by using magnetic resonance signals. Now Lauterbur, "father of the MRI", and Dr. Zhi-Pei Liang have co-authored the first engineering textbook on magnetic resonance imaging. This long-awaited, definitive text will help undergraduate and graduate students of biomedical engineering, biomedical imaging scientists, radiologists, and electrical engineers gain an in-depth understanding of MRI principles. The authors use a signal processing approach to describe the fundamentals of magnetic resonance imaging. You will find a clear and rigorous discussion of these carefully selected essential topics: Mathematical fundamentals Signal generation and detection principles Signal characteristics Signal localization principles Image reconstruction techniques Image contrast mechanisms Image resolution, noise, and artifacts Fast-scan imaging Constrained reconstruction Complete with a comprehensive set of examples and homework problems, Principles of Magnetic Resonance Imaging is the must-read book to improve your knowledge of this revolutionary technique.

Parallel Imaging in Clinical MR Applications

Parallel Imaging in Clinical MR Applications PDF Author: Stefan O. Schönberg
Publisher: Springer Science & Business Media
ISBN: 354068879X
Category : Medical
Languages : en
Pages : 548

Book Description
This book presents the first in-depth introduction to parallel imaging techniques and, in particular, to the application of parallel imaging in clinical MRI. It will provide readers with a broader understanding of the fundamental principles of parallel imaging and of the advantages and disadvantages of specific MR protocols in clinical applications in all parts of the body at 1.5 and 3 Tesla.

Magnetic Resonance Elastography

Magnetic Resonance Elastography PDF Author: Sudhakar K. Venkatesh
Publisher: Springer
ISBN: 1493915754
Category : Medical
Languages : en
Pages : 143

Book Description
The first book to cover the groundbreaking development and clinical applications of Magnetic Resonance Elastography, this book is essential for all practitioners interested in this revolutionary diagnostic modality. The book is divided into three sections. The first covers the history of MRE. The second covers technique and clinical applications of MRE in the liver with respect to fibrosis, liver masses, and other diseases. Case descriptions are presented to give the reader a hands-on approach. The final section presents the techniques, sequence and preliminary results of applications in other areas of the body including muscle, brain, lung, heart, and breast.

Machine Learning for Medical Image Reconstruction

Machine Learning for Medical Image Reconstruction PDF Author: Florian Knoll
Publisher: Springer Nature
ISBN: 3030338436
Category : Computers
Languages : en
Pages : 274

Book Description
This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 24 full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging; deep learning for computed tomography; and deep learning for general image reconstruction.

Compressed Sensing for Magnetic Resonance Image Reconstruction

Compressed Sensing for Magnetic Resonance Image Reconstruction PDF Author: Angshul Majumdar
Publisher: Cambridge University Press
ISBN: 1107103762
Category : Computers
Languages : en
Pages : 227

Book Description
"Discusses different ways to use existing mathematical techniques to solve compressed sensing problems"--Provided by publisher.

Machine Learning for Tomographic Imaging

Machine Learning for Tomographic Imaging PDF Author: Ge Wang
Publisher: Programme: Iop Expanding Physi
ISBN: 9780750322140
Category : Technology & Engineering
Languages : en
Pages : 250

Book Description
Machine learning represents a paradigm shift in tomographic imaging, and image reconstruction is a new frontier of machine learning. This book will meet the needs of those who want to catch the wave of smart imaging. The book targets graduate students and researchers in the imaging community. Open network software, working datasets, and multimedia will be included. The first of its kind in the emerging field of deep reconstruction and deep imaging, Machine Learning for Tomographic Imaging presents the most essential elements, latest progresses and an in-depth perspective on this important topic.

Medical Image Reconstruction

Medical Image Reconstruction PDF Author: Gengsheng Zeng
Publisher: Springer Science & Business Media
ISBN: 3642053688
Category : Technology & Engineering
Languages : en
Pages : 204

Book Description
"Medical Image Reconstruction: A Conceptual Tutorial" introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l0-minimization are also included. This book is written for engineers and researchers in the field of biomedical engineering specializing in medical imaging and image processing with image reconstruction. Gengsheng Lawrence Zeng is an expert in the development of medical image reconstruction algorithms and is a professor at the Department of Radiology, University of Utah, Salt Lake City, Utah, USA.

MRI

MRI PDF Author: Angshul Majumdar
Publisher: CRC Press
ISBN: 1482298899
Category : Technology & Engineering
Languages : en
Pages : 222

Book Description
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.

Quantitative Magnetic Resonance Imaging

Quantitative Magnetic Resonance Imaging PDF Author: Nicole Seiberlich
Publisher: Academic Press
ISBN: 0128170581
Category : Computers
Languages : en
Pages : 1094

Book Description
Quantitative Magnetic Resonance Imaging is a 'go-to' reference for methods and applications of quantitative magnetic resonance imaging, with specific sections on Relaxometry, Perfusion, and Diffusion. Each section will start with an explanation of the basic techniques for mapping the tissue property in question, including a description of the challenges that arise when using these basic approaches. For properties which can be measured in multiple ways, each of these basic methods will be described in separate chapters. Following the basics, a chapter in each section presents more advanced and recently proposed techniques for quantitative tissue property mapping, with a concluding chapter on clinical applications. The reader will learn: - The basic physics behind tissue property mapping - How to implement basic pulse sequences for the quantitative measurement of tissue properties - The strengths and limitations to the basic and more rapid methods for mapping the magnetic relaxation properties T1, T2, and T2* - The pros and cons for different approaches to mapping perfusion - The methods of Diffusion-weighted imaging and how this approach can be used to generate diffusion tensor - maps and more complex representations of diffusion - How flow, magneto-electric tissue property, fat fraction, exchange, elastography, and temperature mapping are performed - How fast imaging approaches including parallel imaging, compressed sensing, and Magnetic Resonance - Fingerprinting can be used to accelerate or improve tissue property mapping schemes - How tissue property mapping is used clinically in different organs - Structured to cater for MRI researchers and graduate students with a wide variety of backgrounds - Explains basic methods for quantitatively measuring tissue properties with MRI - including T1, T2, perfusion, diffusion, fat and iron fraction, elastography, flow, susceptibility - enabling the implementation of pulse sequences to perform measurements - Shows the limitations of the techniques and explains the challenges to the clinical adoption of these traditional methods, presenting the latest research in rapid quantitative imaging which has the possibility to tackle these challenges - Each section contains a chapter explaining the basics of novel ideas for quantitative mapping, such as compressed sensing and Magnetic Resonance Fingerprinting-based approaches