Non Cartesian Parallel Magnetic Resonance Imaging
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Non Cartesian Parallel Magnetic Resonance Imaging
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Author : Robin Heidemann
language : en
Publisher:
Release Date : 2007
Non Cartesian Parallel Magnetic Resonance Imaging written by Robin Heidemann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Advances In Non Cartesian Parallel Magnetic Resonance Imaging Using The Grappa Operator
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Author : Nicole Seiberlich
language : en
Publisher:
Release Date : 2008
Advances In Non Cartesian Parallel Magnetic Resonance Imaging Using The Grappa Operator written by Nicole Seiberlich and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
Magnetic Resonance Imaging With Nonlinear Gradient Fields
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Author : Gerrit Schultz
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-04
Magnetic Resonance Imaging With Nonlinear Gradient Fields written by Gerrit Schultz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-04 with Technology & Engineering categories.
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.
Magnetic Resonance Image Reconstruction
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Author : Mehmet Akcakaya
language : en
Publisher: Academic Press
Release Date : 2022-11-04
Magnetic Resonance Image Reconstruction written by Mehmet Akcakaya and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-04 with Science categories.
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“/li> 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
Advances In Parallel Imaging Reconstruction Techniques
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Author : Peng Qu
language : en
Publisher:
Release Date : 2017-01-27
Advances In Parallel Imaging Reconstruction Techniques written by Peng Qu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with categories.
This dissertation, "Advances in Parallel Imaging Reconstruction Techniques" by Peng, Qu, 瞿蓬, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled Advances in Parallel Imaging Reconstruction Techniques submitted by Qu Peng for the degree of Doctor of Philosophy at The University of Hong Kong in February 2006 In recent years, a new approach to magnetic resonance imaging (MRI), known as "parallel imaging," has revolutionized the field of fast MRI. By using sensitivity information from an RF coil array to perform some of the spatial encoding which is traditionally accomplished by magnetic field gradient, parallel imaging techniques allow reduction of phase encoding steps and consequently decrease the scan time. This thesis presents the author''s investigations in the reconstruction techniques of parallel MRI. After reviewing the conventional methods, such as the image-domain-based sensitivity encoding (SENSE), the k-space-based simultaneous acquisition of spatial harmonics (SMASH), generalized auto-calibrating partially parallel acquisition (GRAPPA), and the iterative SENSE method which is applicable to arbitrary k-space trajectories, the author proposes several advanced reconstruction strategies to enhance the performance of parallel imaging in terms of signal-to-noise (SNR), the power of aliasing artifacts, and computational efficiency. First, the conventional GRAPPA technique is extended in that the data interpolation scheme is tailored and optimized for each specific reconstruction. This novel approach extracts a subset of signal points corresponding to the most linearly independent base vectors in the coefficient matrix for the fit procedure, effectively preventing incorporating redundant signals which only bring noise into reconstruction with little contribution to the exactness of fit. Phantom and in vivo MRI experiments demonstrate that this subset selection strategy can reduce residual artifacts for GRAPPA reconstruction. Second, a novel discrepancy-based method for regularization parameter choice is introduced into GRAPPA reconstruction. By this strategy, adaptive regularization in GRAPPA can be realized which can automatically choose nearly optimal parameters for the reconstructions so as to achieve good compromise between SNR and artifacts. It is demonstrated by MRI experiments that the discrepancy-based parameter choice strategy significantly outperforms those based on the L-curve or on a fixed singular value threshold. Third, the convergence behavior of the iterative non-Cartesian SENSE reconstruction is analyzed, and two different strategies are proposed to make reconstructions more stable and robust. One idea is to stop the iteration process in due time so that artifacts and SNR are well balanced and fine overall image quality is achieved; as an alternative, the inner-regularization method, in combination with the Lanczos iteration process, is introduced into non-Cartesian SENSE to mitigate the ill-conditioning effect and improve the convergence behavior. Finally, a novel multi-resolution successive iteration (MRSI) algorithm for non-Cartesian parallel imaging is proposed. The conjugate gradient (CG) iteration is performed in several successive phases with increasing resolution. It is demonstrated by spiral MRI results that the total reconstruction time can be reduced by over 30% by using low resolution in initial stages of iteration. In sum, the author describes several developments in image reconstruction for sensitivity-encoded MRI. The great potential of parallel imaging in modern applications can be further enh
Quantitative Magnetic Resonance Imaging
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Author : Nicole Seiberlich
language : en
Publisher: Academic Press
Release Date : 2020-11-18
Quantitative Magnetic Resonance Imaging written by Nicole Seiberlich and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-18 with Computers categories.
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
Magnetic Resonance Angiography Using Non Cartesian Trajectories
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Author : Kie Tae Kwon
language : en
Publisher:
Release Date : 2015
Magnetic Resonance Angiography Using Non Cartesian Trajectories written by Kie Tae Kwon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Magnetic resonance imaging (MRI) is a versatile medical imaging modality that provides excellent soft-tissue contrast without ionizing radiation. Magnetic resonance angiography (MRA) is a type of MRI that is specifically aimed to image blood vessels, and is a powerful clinical tool for the diagnosis and management of arterial diseases. Various techniques can be used for MRA to produce bright blood signals while suppressing background signals such as muscle and fat. This dissertation describes two MRA methods that use non-Cartesian k-space trajectories to improve the contrast between the arterial signals and the background signals while achieving shorter scan times than conventional approaches. The ultimate goal of this work is to make MRA more clinically practical and reliable in terms of scan time and diagnostic image quality. The first method is a non-contrast-enhanced peripheral MRA sequence using a 3D concentric cylinders trajectory. The concentric cylinders are acquired in a sliding interleaved manner over a series of thin slabs. Concentric cylinders enable improved scan time efficiency while providing less noticeable artifacts from k-space amplitude modulation compared to a conventional Cartesian sequence. The thin-slab-scan nature of the proposed sequence and the centric-ordered sampling geometry of concentric cylinders are exploited to implement efficient fluid-suppression and parallel imaging approaches. In vivo experiments in healthy subjects and a patient with arterial stenosis demonstrate that the proposed method can provide improved artery-vein contrast even with slow arterial flow. The second method is a first-pass contrast-enhanced coronary MRA sequence using a 2D spiral-ring trajectory. In addition to the speed inherited from a regular spiral trajectory, the spiral-ring trajectory is capable of effectively capturing transient contrast generated by the first-pass contrast agent. The centric-ordered structure of the spiral-ring trajectory is exploited to efficiently generate time-resolved datasets, which makes the sequence more robust to the variation of the timing of contrast bolus and more flexible to capture different contrast fillings in different coronary branches. In vivo experiments in healthy subjects and patients demonstrate that the proposed method can provide improved blood-muscle contrast within a single breath-hold.
Reconstruction Methods For Exploiting Non Cartesian Steady State Mr Imaging
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Author : Youngkyoo Jung
language : en
Publisher:
Release Date : 2007
Reconstruction Methods For Exploiting Non Cartesian Steady State Mr Imaging written by Youngkyoo Jung and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Parallelism Patterns And Performance In Iterative Mri Reconstruction
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Author : Mark Murphy
language : en
Publisher:
Release Date : 2011
Parallelism Patterns And Performance In Iterative Mri Reconstruction written by Mark Murphy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Magnetic Resonance Imaging (MRI) is a non-invasive and highly flexible medical imaging modality that does not expose patients ionizing radiation. MR Image acquisitions can be designed by varying a large number of contrast-generation parameters, and many clinical diagnostic applications exist. However, imaging speed is a fundamental limitation to many potential applications. Traditionally, MRI data have been collected at Nyquist sampling rates to produce alias-free images. However, many recent scan acceleration techniques produce sub-Nyquist samplings. For example, Parallel Imaging is a well-established acceleration technique that receives the MR signal simultaneously from multiple receive channels. Compressed sensing leverages randomized undersampling and the compressibility (e.g. via Wavelet transforms or Total-Variation) of medical images to allow more aggressive undersampling. Reconstruction of clinically viable images from these highly accelerated acquisitions requires powerful, usually iterative algorithms. Non-Cartesian pulse sequences that perform non-equispaced sampling of k-space further increase computational intensity of reconstruction, as they preclude direct use of the Fast Fourier Transform (FFT). Most iterative algorithms can be understood by considering the MRI reconstruction as an inverse problem, where measurements of un-observable parameters are made via an observation function that models the acquisition process. Traditional direct reconstruction methods attempt to invert this observation function, whereas iterative methods require its repeated computation and computation of its adjoint. As a result, na\"ive sequential implementations of iterative reconstructions produce unfeasibly long runtimes. Their computational intensity is a substantial barrier to their adoption in clinical MRI practice. A powerful new family of massively parallel microprocessor architectures has emerged simultaneously with the development of these new reconstruction techniques. Due to fundamental limitations in silicon fabrication technology, sequential microprocessors reached the power-dissipation limits of commodity cooling systems in the early 2000's. The techniques used by processor architects to extract instruction-level parallelism from sequential programs face ever-diminishing returns, and further performance improvement of sequential processors via increasing clock-frequency has become impractical. However, circuit density and process feature sizes still improve at Moore's Law rates. With every generation of silicon fabrication technology, a larger number of transistors are available to system architects. Consequently, all microprocessor vendors now exclusively produce multi-core parallel processors. Additionally, the move towards on-chip parallelism has allowed processor architects a larger degree of freedom in the design of multi-threaded pipelines and memory hierarchies. Many of the inefficiencies inherent in superscalar out-of-order design are being replaced by the high efficiency afforded by throughput-oriented designs. The move towards on-chip parallelism has resulted in a vast increase in the amount of computational power available in commodity systems. However, this move has also shifted the burden of computational performance towards software developers. In particular, the highly efficient implementation of MRI reconstructions on these systems requires manual parallelization and optimization. Thus, while ubiquitous parallelism provides a solution to the computational intensity of iterative MRI reconstructions, it also poses a substantial software productivity challenge. In this thesis, we propose that a principled approach to the design and implementation of reconstruction algorithms can ameliorate this software productivity issue. We draw much inspiration from developments in the field of computational science, which has faced similar parallelization and software development challenges for several decades. We propose a Software Architecture for the implementation of reconstruction algorithms, which composes two Design Patterns that originated in the domain of massively parallel scientific computing. This architecture allows for the most computationally intense operations performed by MRI reconstructions to be implemented as re-usable libraries. Thus the software development effort required to produce highly efficient and heavily optimized implementations of these operations can be amortized over many different reconstruction systems. Additionally, the architecture prescribes several different strategies for mapping reconstruction algorithms onto parallel processors, easing the burden of parallelization. We describe the implementation of a complete reconstruction, $\ell_1$-SPIRiT, according to these strategies. $\ell_1$-SPIRiT is a general reconstruction framework that seamlessly integrates all three of the scan acceleration techniques mentioned above. Our implementation achieves substantial performance improvement over baseline, and has enabled substantial clinical evaluation of its approach to combining Parallel Imaging and Compressive Sensing. Additionally, we include an in-depth description of the performance optimization of the non-uniform Fast Fourier Transform (nuFFT), an operation used in all non-Cartesian reconstructions. This discussion complements well our description of $\ell_1$-SPIRiT, which we have only implemented for Cartesian samplings.
Accelerated Dynamic Magnetic Resonance Imaging
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Author : Jennifer Steeden
language : en
Publisher: Academic Press
Release Date : 2023-09-01
Accelerated Dynamic Magnetic Resonance Imaging written by Jennifer Steeden and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-01 with Science categories.
Magnetic Resonance Imaging (MRI) scans play a vital role in diagnosis and monitoring of diseases across the body. However, MRI is a relatively slow imaging technology, resulting in long scan times. This is particularly challenging when imaging dynamic processes. Accelerated Dynamic Magnetic Resonance Imaging: Methods and Applications explains the technologies which can speed up MRI imaging and shows how they have been applied to a broad range of application areas, presenting the challenges and giving practical advice on implementation. With this book the reader will be able to: Modify the MRI sequences to speed up acquisition of data (non-Cartesian trajectories and data under sampling); Use the techniques (parallel imaging, compressed sensing and machine learning) which are commonly used to reconstruct under sampled MRI data; Implement fast MRI imaging techniques for their application areas. Accelerated Dynamic Magnetic Resonance Imaging: Methods and Applications is an ideal resource for the technologist, clinical researcher and clinician who want to understand rapid MRI methods and gain practical advice on their implementation.