Regularized Image Reconstruction In Parallel Mri With Matlab
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Regularized Image Reconstruction In Parallel Mri With Matlab
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Author : Joseph Suresh Paul
language : en
Publisher: CRC Press
Release Date : 2019-11-05
Regularized Image Reconstruction In Parallel Mri With Matlab written by Joseph Suresh Paul and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-05 with Medical categories.
Regularization becomes an integral part of the reconstruction process in accelerated parallel magnetic resonance imaging (pMRI) due to the need for utilizing the most discriminative information in the form of parsimonious models to generate high quality images with reduced noise and artifacts. Apart from providing a detailed overview and implementation details of various pMRI reconstruction methods, Regularized image reconstruction in parallel MRI with MATLAB examples interprets regularized image reconstruction in pMRI as a means to effectively control the balance between two specific types of error signals to either improve the accuracy in estimation of missing samples, or speed up the estimation process. The first type corresponds to the modeling error between acquired and their estimated values. The second type arises due to the perturbation of k-space values in autocalibration methods or sparse approximation in the compressed sensing based reconstruction model. Features: Provides details for optimizing regularization parameters in each type of reconstruction. Presents comparison of regularization approaches for each type of pMRI reconstruction. Includes discussion of case studies using clinically acquired data. MATLAB codes are provided for each reconstruction type. Contains method-wise description of adapting regularization to optimize speed and accuracy. This book serves as a reference material for researchers and students involved in development of pMRI reconstruction methods. Industry practitioners concerned with how to apply regularization in pMRI reconstruction will find this book most useful.
Parallel Mri
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Author : Hammad Omer
language : en
Publisher:
Release Date : 2012
Parallel Mri written by Hammad Omer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Magnetic Resonance Imaging (MRI) is a non-ionising imaging modality which can provide excellent soft-tissue contrast because of a large number of flexible contrast parameters. One major limitation of MRI is its long acquisition time. Parallel MRI provides a framework to reduce the scan time. The aim of this thesis is to investigate and develop new methods to improve the performance of Parallel MRI. A new GUI (Graphical User Interface) based platform is developed using Matlab which provides an interactive environment to apply different Parallel MRI algorithms as well as helps to analyse the results. Regularization based reconstruction in Parallel MRI utilizes some prior information about the image to achieve better reconstruction results. The use of regularization in Parallel MRI is investigated and a new algorithm is proposed which uses wavelet-denoising of the coil sensitivity estimates before applying SENSE (a Parallel MRI algorithm). The results show that the proposed method is computationally efficient and offers a good alternative to regularization for lower acceleration factors (AF) in Parallel MRI. A good choice of the regularization parameter in regularization based Parallel MRI reconstructions plays a pivotal role to have good results. A new algorithm to choose the regularization parameter efficiently has been developed. This method uses the g-Factor (noise amplification parameter in Parallel MRI) as a regularization parameter and provides better reconstruction results than the contemporary methods. The proposed algorithm improves the computational efficiency of regularization based reconstructions in Parallel MRI. The use of Parallel MRI in interventional imaging can greatly reduce the time required for imaging. A novel catheter based phased array coil, composed of two independent coil elements has been developed. This phased array receiver coil can implement Parallel MRI. Some initial imaging experiments using this coil system have been performed and the results show a successful implementation of Parallel MRI on the acquired data.
Computer Science For Environmental Engineering And Ecoinformatics
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Author : Yuanxu Yu
language : en
Publisher: Springer
Release Date : 2011-07-18
Computer Science For Environmental Engineering And Ecoinformatics written by Yuanxu Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-18 with Computers categories.
This two-volume set (CCIS 158 and CCIS 159) constitutes the refereed proceedings of the International Workshop on Computer Science for Environmental Engineering and EcoInformatics, CSEEE 2011, held in Kunming, China, in July 2011. The 150 revised full papers presented in both volumes were carefully reviewed and selected from a large number of submissions. The papers are organized in topical sections on computational intelligence; computer simulation; computing practices and applications; ecoinformatics; image processing information retrieval; pattern recognition; wireless communication and mobile computing; artificial intelligence and pattern classification; computer networks and Web; computer software, data handling and applications; data communications; data mining; data processing and simulation; information systems; knowledge data engineering; multimedia applications.
Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms
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Author : Bhabesh Deka
language : en
Publisher: Springer
Release Date : 2018-12-29
Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms written by Bhabesh Deka and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-29 with Technology & Engineering categories.
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.
Compressed Sensing For Engineers
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Author : Angshul Majumdar
language : en
Publisher: CRC Press
Release Date : 2018-12-07
Compressed Sensing For Engineers written by Angshul Majumdar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Technology & Engineering categories.
Compressed Sensing (CS) in theory deals with the problem of recovering a sparse signal from an under-determined system of linear equations. The topic is of immense practical significance since all naturally occurring signals can be sparsely represented in some domain. In recent years, CS has helped reduce scan time in Magnetic Resonance Imaging (making scans more feasible for pediatric and geriatric subjects) and has also helped reduce the health hazard in X-Ray Computed CT. This book is a valuable resource suitable for an engineering student in signal processing and requires a basic understanding of signal processing and linear algebra. Covers fundamental concepts of compressed sensing Makes subject matter accessible for engineers of various levels Focuses on algorithms including group-sparsity and row-sparsity, as well as applications to computational imaging, medical imaging, biomedical signal processing, and machine learning Includes MATLAB examples for further development
Parallel Magnetic Resonance Imaging Reconstruction Problems Using Wavelet Representations
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Author : Lotfi Chaari (enseignant-chercheur en informatique).)
language : en
Publisher:
Release Date : 2010
Parallel Magnetic Resonance Imaging Reconstruction Problems Using Wavelet Representations written by Lotfi Chaari (enseignant-chercheur en informatique).) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
To reduce scanning time or improve spatio-temporal resolution in some MRI applications, parallel MRI acquisition techniques with multiple coils have emerged since the early 90's as powerful methods. In these techniques, MRI images have to be reconstructed from acquired undersampled « k-space » data. To this end, several reconstruction techniques have been proposed such as the widely-used SENSitivity Encoding (SENSE) method. However, the reconstructed images generally present artifacts due to the noise corrupting the observed data and coil sensitivity profile estimation errors. In this work, we present novel SENSE-based reconstruction methods which proceed with regularization in the complex wavelet domain so as to promote the sparsity of the solution. These methods achieve accurate image reconstruction under degraded experimental conditions, in which neither the SENSE method nor standard regularized methods (e.g. Tikhonov) give convincing results. The proposed approaches relies on fast parallel optimization algorithms dealing with convex but non-differentiable criteria involving suitable sparsity promoting priors. Moreover, in contrast with most of the available reconstruction methods which proceed by a slice by slice reconstruction, one of the proposed methods allows 4D (3D + time) reconstruction exploiting spatial and temporal correlations. The hyperparameter estimation problem inherent to the regularization process has also been addressed from a Bayesian viewpoint by using MCMC techniques. Experiments on real anatomical and functional data show that the proposed methods allow us to reduce reconstruction artifacts and improve the statistical sensitivity/specificity in functional MRI.
Determination Of Regularization Parameters For Parallel Imaging Reconstruction Using Wavelet Priors
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Author : Roxanne Ludwigson
language : en
Publisher:
Release Date : 2008
Determination Of Regularization Parameters For Parallel Imaging Reconstruction Using Wavelet Priors written by Roxanne Ludwigson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Image reconstruction categories.
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
Reconstruction Of Parallel Magnetic Resonance Imaging Images Using High Resolution Image Reconstruction Techniques
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Author : Chi Kin Tai
language : en
Publisher:
Release Date : 2010
Reconstruction Of Parallel Magnetic Resonance Imaging Images Using High Resolution Image Reconstruction Techniques written by Chi Kin Tai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Magnetic resonance imaging categories.
Improvement In High Acceleration Parallel Magnetic Resonance Imaging Using Efficient Graph Based Energy Minimization Methods
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Author : Gurmeet Singh
language : en
Publisher:
Release Date : 2008
Improvement In High Acceleration Parallel Magnetic Resonance Imaging Using Efficient Graph Based Energy Minimization Methods written by Gurmeet Singh 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.