Méthodologies pour l'imagerie par résonance magnétique utilisant la technique de projection-reconstruction PDF Download
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Author: Yannick Crémillieux
Publisher:
ISBN:
Category :
Languages : fr
Pages :
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Author: Yannick Crémillieux
Publisher:
ISBN:
Category :
Languages : fr
Pages :
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Author: Ralf Lethmate
Publisher:
ISBN:
Category :
Languages : en
Pages : 199
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Book Description
Récemment, un fort regain d'intérêt pour les techniques d'échantillonnage radia en Imagerie de Résonance Magnétique (IRM) est perceptible. Elles permettent d'imager des objets ayant des temps de relaxation transversal très courts et sont peu sensibles aux mouvements. Nous proposons dans ce travail 1) de nouvelles stratégies d'échantillonnage radial 2D/3D et 2) des algorithmes avancés de reconstruction d'image IRM, tels que la techniques de "gridding" utilisant des compensations de densité original, les méthodes Bayésiennes et BURS. Ces algorithmes constituent une avancée considérable dans le monde IRM puisque la reconstruction d'image est possible à partir de tout échantillonnage. Pour augmenter l'intensité du signal, il est avantageux de l'échantillonner dès la montée des gradients, les positions des échantillons diffèrent alors des positions idéales des distributions utilisées (Projection Reconstruction (PR-2D) et linogramme). Or, la reconstruction de l'image nécessite la connaissance précise de ces dernières, qui peuvent être estimées grâce à une expérience préliminaire ou une approche fondée sur la transformation de Gabor. En imagerie 3D, nous proposons cinq équidistributions isotropes que nous comparons à la technique PR-3D, qui souffre d'un sur-échantillonnage excessif sur les pôles. Nous avons mis l'accent sur la qualité d'image, la facilité d'implantation sur l'imageur et els temps d'acquisition qui peuvent ainsi être réduits de 30%. À notre connaissance, ces équidistributions n'ont jamais été appliquées à l'IRM auparavant. Nous proposons également une nouvelle méthode d'imagerie dynamique 3D, prometteuse pour l'angiographie, l'imagerie de perfusion, etc. Elle est fondée sur ces équidistributions et utilise une nouvelle approche "keyhole-sphérique". Tout en ajoutant la dimension temporelle, le temps d'acquisition reste identique à celui d'une acquisition radiale 3D classique. Les résultats sont présentés pour des pseudo-données et des données réelles.
Author: Mehmet Akcakaya
Publisher: Academic Press
ISBN: 012822746X
Category : Science
Languages : en
Pages : 518
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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
Author: Bhabesh Deka
Publisher: Springer
ISBN: 9811335974
Category : Technology & Engineering
Languages : en
Pages : 133
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Book Description
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.
Author: Joseph Suresh Paul
Publisher: CRC Press
ISBN: 1351029258
Category : Medical
Languages : en
Pages : 306
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Book Description
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.
Author: Alan B. McMillan
Publisher:
ISBN:
Category :
Languages : en
Pages : 164
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Author: Jean-Paul Vallée
Publisher:
ISBN:
Category :
Languages : en
Pages : 250
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Book Description
Cette thèse décrit une approche originale de mesure de la perfusion tissulaire basée sur l'imagerie par résonance magnétique (IRM) et l'injection intraveineuse de produits de contraste. Les grands principes de la technique d'IRM ainsi que les différentes classes de produits de contraste sont passés en revue. Puis, les séquences d'impulsions RF utilisées pour la mesure de la perfusion tissulaire sont étudiées, suivies des méthodes de conversion du signal en concentration de produit de contraste. Enfin, la dernière partie présente deux classes de modèles permettant de mesurer la perfusion tissulaire à partir des courbes de transit obtenues avec l'IRM qui ont été développées durant cette thèse. La méthode proposée dans cette thèse démontre qu'il est possible de mesurer d'une manière non invasive par IRM le débit de perfusion tissulaire ainsi que cela a été vérifié dans quelques situations cliniques.
Author: Marinus T. Vlaardingerbroek
Publisher: Springer Science & Business Media
ISBN: 3662052520
Category : Science
Languages : en
Pages : 510
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Book Description
Presents an overall analytical treatment of MRI physics and engineering. Special attention is paid to the treatment of intrinsic artefacts of the different sequences which can be described for the different scan methods. The book contains many images, especially showing specific properties of the different scan methods. The methods discussed include RARE, GRASE, EPI and Spiral Scan. The 3rd edition deals with stranger gradient and new RF coil systems, and sequences such as Balanced FFE and q-space diffusion imaging and SENSE.
Author: Sumit Datta
Publisher:
ISBN: 9789811335983
Category : Compressed sensing (Telecommunication)
Languages : en
Pages : 133
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Book Description
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.
Author: Angshul Majumdar
Publisher:
ISBN: 9781316675182
Category : Algorithms
Languages : en
Pages :
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Book Description
Expecting the reader to have some basic training in liner algebra and optimization, the book begins with a general discussion on CS techniques and algorithms. It moves on to discussing single channel static MRI, the most common modality in clinical studies. It then takes up multi-channel MRI and the interesting challenges consequently thrown up in signal reconstruction. Off-line and on-line techniques in dynamic MRI reconstruction are visited. Towards the end the book broadens the subject by discussing how CS is being applied to other areas of biomedical signal processing like X-ray, CT and EEG acquisition. The emphasis throughout is on qualitative understanding of the subject rather than on quantitative aspects of mathematical forms. The book is intended for MRI engineers interested in the brass tacks of image formation; medical physicists interested in advanced techniques in image reconstruction; and mathematicians or signal processing engineers.
