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Author: Yuxin Hu Publisher: ISBN: Category : Languages : en Pages :
Book Description
Diffusion-weighted MRI (DWI) is a non-invasive and non-ionizing method that detects the tissue microstructure by measuring the Brownian motion of water molecules in our body. It plays an essential role in numerous clinical applications and neuroscience research. However, the spatial resolution and signal-to-noise ratio of conventional DWI are limited due to the use of a single-shot acquisition. Multi-shot imaging enables the acquisition of high-resolution DWI data, but results in ghosting artifacts and signal cancellation. In this dissertation, we present advanced reconstruction techniques to overcome these artifacts and enable high-quality DWI in the clinic. First, we present the usage of the locally low-rank regularization to resolve the motion-induced phase variations among different shots. We demonstrate the improvements of multi-shot imaging with our proposed reconstruction in a clinical breast MRI study. To further improve the image quality, we introduce a non-linear model with a constraint on the magnitude images to utilize the angular correlation between different diffusion-encoding directions. Finally, we accelerate the reconstruction with an unrolled pipeline, which contains recurrences of model-based gradient updates and neural networks alternating between image space and Fourier space. Together, these techniques allow immediate reconstruction of high-resolution high-SNR DWI with reduced scan time requirements.
Author: Yuxin Hu Publisher: ISBN: Category : Languages : en Pages :
Book Description
Diffusion-weighted MRI (DWI) is a non-invasive and non-ionizing method that detects the tissue microstructure by measuring the Brownian motion of water molecules in our body. It plays an essential role in numerous clinical applications and neuroscience research. However, the spatial resolution and signal-to-noise ratio of conventional DWI are limited due to the use of a single-shot acquisition. Multi-shot imaging enables the acquisition of high-resolution DWI data, but results in ghosting artifacts and signal cancellation. In this dissertation, we present advanced reconstruction techniques to overcome these artifacts and enable high-quality DWI in the clinic. First, we present the usage of the locally low-rank regularization to resolve the motion-induced phase variations among different shots. We demonstrate the improvements of multi-shot imaging with our proposed reconstruction in a clinical breast MRI study. To further improve the image quality, we introduce a non-linear model with a constraint on the magnitude images to utilize the angular correlation between different diffusion-encoding directions. Finally, we accelerate the reconstruction with an unrolled pipeline, which contains recurrences of model-based gradient updates and neural networks alternating between image space and Fourier space. Together, these techniques allow immediate reconstruction of high-resolution high-SNR DWI with reduced scan time requirements.
Author: Peng Qu Publisher: ISBN: 9781361470411 Category : Languages : en Pages :
Book Description
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
Author: Dow-Mu Koh Publisher: Springer Science & Business Media ISBN: 3540785760 Category : Medical Languages : en Pages : 299
Book Description
It is a great privilege to introduce this book devoted to the current and future roles in research and clinical practice of another exciting new development in MRI: Diffusi- weighted MR imaging. This new, quick and non-invasive technique, which requires no contrast media or i- izing radiation, offers great potential for the detection and characterization of disease in the body as well as for the assessment of tumour response to therapy. Indeed, whereas DW-MRI is already ? rmly established for the study of the brain, progress in MR techn- ogy has only recently enabled its successful application in the body. Although the main focus of this book is on the role of DW-MRI in patients with malignant tumours, n- oncological emerging applications in other conditions are also discussed. The editors of this volume, Dr. D. M. Koh and Prof. H. Thoeny, are internationally well known for their pioneering work in the ? eld and their original contributions to the l- erature on DW-MRI of the body. I am very much indebted to them for the enthusiasm and engagement with which they prepared and edited this splendid volume in a record short time for our series Medical Radiology – Diagnostic section.
Author: Gastão Cruz Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
The proposed method reduced scan times by 2.6x when compared with the gated acquisition while maintaining similar image quality. In the second application, the framework is combined with interleaved image navigators to add high temporal resolution motion correction. This method also presented similar coronary lumen quality to the gated, despite a 1.6x reduction in scan time. Additionally, it presented sig- nificantly superior vessel wall quality when compared to translation correction. In the third application, the framework is combined with Parallel Imaging, Compressed Sensing and interleaved image naviga- tors. Initial results indicate the proposed approach produces signifi- cantly superior water and fat images than translation correction.
Author: Derek K Jones Publisher: Oxford University Press ISBN: 0199708703 Category : Science Languages : en Pages : 784
Book Description
Professor Derek Jones, a world authority on diffusion MRI, has assembled most of the world's leading scientists and clinicians developing and applying diffusion MRI to produce an authorship list that reads like a "Who's Who" of the field and an essential resource for those working with diffusion MRI. Destined to be a modern classic, this definitive and richly illustrated work covers all aspects of diffusion MRI from basic theory to clinical application. Oxford Clinical Neuroscience is a comprehensive, cross-searchable collection of resources offering quick and easy access to eleven of Oxford University Press's prestigious neuroscience texts. Joining Oxford Medicine Online these resources offer students, specialists and clinical researchers the best quality content in an easy-to-access format.
Author: Moo K. Chung Publisher: Cambridge University Press ISBN: 110718486X Category : Computers Languages : en Pages : 343
Book Description
This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.
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.
Author: Denis Le Bihan Publisher: CRC Press ISBN: 0429763492 Category : Medical Languages : en Pages : 563
Book Description
First book ever on the topic Discusses current concepts and methodological issues for the successful implementation of IVIM MRI to investigate tissue perfusion non-invasively Covers a wide range of clinical applications Contributions by leading experts in the field from USA, Europe, and Asia and written with a good balance of methodological and clinical chapters Includes an extensive bibliography for further reading
Author: Yuxin Hu
Author: Yuxin Hu
Author: Aurelien Bustin
Author: John-Paul Leo Sikora
Author: Peng Qu
Author: Dow-Mu Koh
Author: Gastão Cruz
Author: Derek K Jones
Author: Moo K. Chung
Author: Stefan O. Schönberg
Author: Denis Le Bihan