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​Within the past few decades MRI has become one of the most important imaging modalities in medicine. For a reliable diagnosis of pathologies further technological improvements are of primary importance. This study deals with a radically new approach of image encoding. Gradient linearity has ever since been an unquestioned technological design criterion. With the advent of parallel imaging, this approach may be questioned, making way of much a more flexible gradient hardware that uses encoding fields with an arbitrary geometry. The theoretical basis of this new imaging modality – PatLoc imaging – are comprehensively presented, suitable image reconstruction algorithms are developed for a variety of imaging sequences and imaging results – including in vivo data – are explored based on novel hardware designs.
New edition explores contemporary MRI principles and practices Thoroughly revised, updated and expanded, the second edition of Magnetic Resonance Imaging: Physical Principles and Sequence Design remains the preeminent text in its field. Using consistent nomenclature and mathematical notations throughout all the chapters, this new edition carefully explains the physical principles of magnetic resonance imaging design and implementation. In addition, detailed figures and MR images enable readers to better grasp core concepts, methods, and applications. Magnetic Resonance Imaging, Second Edition begins with an introduction to fundamental principles, with coverage of magnetization, relaxation, quantum mechanics, signal detection and acquisition, Fourier imaging, image reconstruction, contrast, signal, and noise. The second part of the text explores MRI methods and applications, including fast imaging, water-fat separation, steady state gradient echo imaging, echo planar imaging, diffusion-weighted imaging, and induced magnetism. Lastly, the text discusses important hardware issues and parallel imaging. Readers familiar with the first edition will find much new material, including: New chapter dedicated to parallel imaging New sections examining off-resonance excitation principles, contrast optimization in fast steady-state incoherent imaging, and efficient lower-dimension analogues for discrete Fourier transforms in echo planar imaging applications Enhanced sections pertaining to Fourier transforms, filter effects on image resolution, and Bloch equation solutions when both rf pulse and slice select gradient fields are present Valuable improvements throughout with respect to equations, formulas, and text New and updated problems to test further the readers' grasp of core concepts Three appendices at the end of the text offer review material for basic electromagnetism and statistics as well as a list of acquisition parameters for the images in the book. Acclaimed by both students and instructors, the second edition of Magnetic Resonance Imaging offers the most comprehensive and approachable introduction to the physics and the applications of magnetic resonance imaging.
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
This book is designed to introduce the reader to the field of NMR/MRI at very low magnetic fields, from milli-Tesla to micro-Tesla, the ultra-low field (ULF) regime. The book is focused on applications to imaging the human brain, and hardware methods primarily based upon pre-polarization methods and SQUID-based detection. The goal of the text is to provide insight and tools for the reader to better understand what applications are best served by ULF NMR/MRI approaches. A discussion of the hardware challenges, such as shielding, operation of SQUID sensors in a dynamic field environment, and pulsed magnetic field generation are presented. One goal of the text is to provide the reader a framework of understanding the approaches to estimation and mitigation of low signal-to-noise and long imaging time, which are the main challenges. Special attention is paid to the combination of MEG and ULF MRI, and the benefits and challenges presented by trying to accomplish both with the same hardware. The book discusses the origin of unique relaxation contrast at ULF, and special considerations for image artifacts and how to correct them (i.e. concomitant gradients, ghost artifacts). A general discussion of MRI, with special consideration to the challenges of imaging at ULF and unique opportunities in pulse sequences, is presented. The book also presents an overview of some of the primary applications of ULF NMR/MRI being pursued.
Abstract: The goal of this thesis was to design, implement and test a shielded matrix gradient coil for magnetic resonance imaging (MRI). The design process addressed gradient strength, flexibility, magnetic shielding, cooling, electrical decoupling, balance of force and torque and patient safety. These demands were fulfilled by designing two different coil element types which form a cylindrical coil configuration containing two main current carrying surfaces and a shared shielding surface. For manufacturing and handling reasons the coil elements were designed such that each coil element can be manufactured and tested individually. Scaling the dimensions of a whole-body gradient coil to an insert coil led to a total of 7 rings with 12 elements each, summing up to a total of 84 elements. The resulting modular design led to a successful patent application. All 84 coil element channels were manufactured in-house using a powder bed ink-jet head 3D printing technology and assembled with the water cooling. Before integrating the realized matrix coil prototype into a 3T MRI environment, its electrical and thermal behavior was characterized experimentally. The gradient strength, eddy current behavior, acoustic response and the resulting field maps were characterized within the scanner environment. Established imaging methods were implemented and the resulting images prove the successful realization and integration of the coil. In vivo imaging experiments were performed after a satisfying safety assessment. The flexibility regarding the realizable nonlinear spatial encoding magnetic field (SEM) shapes of the realized coil prototype allows for novel imaging methodologies. This is demonstrated in this thesis by deploying such SEM for simultaneous multislice imaging. The simultaneous excitation of multiple slices with standard single-band radio frequency pulses was explored. Additionally frequency shifting of signals from different slices was demonstrated, which in principle allows for parallel imaging without additional information from radio frequency receiver array coils
This book presents a comprehensive review of the recent developments in fast L1-norm regularization-based compressed sensing (CS) magnetic resonance image reconstruction algorithms. Compressed sensing magnetic resonance imaging (CS-MRI) is able to reduce the scan time of MRI considerably as it is possible to reconstruct MR images from only a few measurements in the k-space; far below the requirements of the Nyquist sampling rate. L1-norm-based regularization problems can be solved efficiently using the state-of-the-art convex optimization techniques, which in general outperform the greedy techniques in terms of quality of reconstructions. Recently, fast convex optimization based reconstruction algorithms have been developed which are also able to achieve the benchmarks for the use of CS-MRI in clinical practice. This book enables graduate students, researchers, and medical practitioners working in the field of medical image processing, particularly in MRI to understand the need for the CS in MRI, and thereby how it could revolutionize the soft tissue imaging to benefit healthcare technology without making major changes in the existing scanner hardware. It would be particularly useful for researchers who have just entered into the exciting field of CS-MRI and would like to quickly go through the developments to date without diving into the detailed mathematical analysis. Finally, it also discusses recent trends and future research directions for implementation of CS-MRI in clinical practice, particularly in Bio- and Neuro-informatics applications.