Skip to main content

Diffusion Mri And Microstructure

In Order to Read Online or Download Diffusion Mri And Microstructure Full eBooks in PDF, EPUB, Tuebl and Mobi you need to create a Free account. Get any books you like and read everywhere you want. Fast Download Speed ~ Commercial & Ad Free. We cannot guarantee that every book is in the library!

Advanced Diffusion MRI for Microstructure Imaging

Advanced Diffusion MRI for Microstructure Imaging Book
Author : A. Savickas
Publisher : Unknown
Release : 2016
ISBN : 0987650XXX
Language : En, Es, Fr & De

GET BOOK

Book Description :

Download Advanced Diffusion MRI for Microstructure Imaging book written by A. Savickas, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Assessing Cellular Microstructure in Biological Tissues using In Vivo Diffusion Weighted Magnetic Resonance

Assessing Cellular Microstructure in Biological Tissues using In Vivo Diffusion Weighted Magnetic Resonance Book
Author : Julien Valette,Itamar Ronen,Sune Nørhøj Jespersen
Publisher : Frontiers Media SA
Release : 2019-05-16
ISBN : 2889458415
Language : En, Es, Fr & De

GET BOOK

Book Description :

Magnetic resonance imaging (MRI) and spectroscopy (MRS) techniques have opened new doors for examining biological tissues in vivo. By combining sensitization to diffusion using magnetic field gradients with a variety of imaging and localization schemes, diffusion-weighted MRI and diffusion-weighted MRS allow investigating translational diffusion of endogenous molecules, such as water or metabolites, in biological tissues, most commonly the brain but also other organs such as the prostate. The typical voxel resolution of MRI or MRS is in the millimeter to centimeter range, much lower than the cellular scale. However, as molecules are typically diffusing over just a few µm during the duration of the measurement (the “diffusion time”) and encounter numerous biological membranes at these scales, the average cellular microstructure has a critical influence on the measured diffusion signal. Hence, diffusion-weighted MRI and diffusion-weighted MRS are sensitive to tissue microstructure at a scale well below the nominal imaging resolution. However, the connection between diffusion properties and tissue microstructure remains indirect, so any attempt to quantify microstructure will rely on modeling. The goal of this Research Topic was to gather experts in various acquisition and modeling strategies and show how these approaches, despite their own strengths and weaknesses, can yield unique information about cellular microstructure, and sometimes complement each other.

Characterizing Microstructure of Porous Media Using Noble gas diffusion MRI at Short Time Scales

Characterizing Microstructure of Porous Media Using Noble gas diffusion MRI at Short Time Scales Book
Author : Michael Carl
Publisher : Unknown
Release : 2008
ISBN : 9780549797333
Language : En, Es, Fr & De

GET BOOK

Book Description :

Simulations were conducted using a 3D digital lung model, to investigate the sensitivity of diffusion measurements at different diffusion timescales to the progression of emphysema. The behavior of the diffusivity at short diffusion times was found to be a sensitive measure for destruction of the alveoli.

Advanced Diffusion MRI in Brain Tumors

Advanced Diffusion MRI in Brain Tumors Book
Author : Antonella Castellano
Publisher : Unknown
Release : 2014
ISBN : 0987650XXX
Language : En, Es, Fr & De

GET BOOK

Book Description :

Download Advanced Diffusion MRI in Brain Tumors book written by Antonella Castellano, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Biophysical Modelling in Diffusion MRI

Biophysical Modelling in Diffusion MRI Book
Author : Anonim
Publisher : Unknown
Release : 2011
ISBN : 9789174731699
Language : En, Es, Fr & De

GET BOOK

Book Description :

Download Biophysical Modelling in Diffusion MRI book written by , available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Diffusion Tensor Imaging

Diffusion Tensor Imaging Book
Author : Wim Van Hecke,Louise Emsell,Stefan Sunaert
Publisher : Springer
Release : 2015-12-14
ISBN : 1493931180
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book provides an overview of the practical aspects of diffusion tensor imaging (DTI), from understanding the basis of the technique through selection of the right protocols, trouble-shooting data quality, and analyzing DTI data optimally. DTI is a non-invasive magnetic resonance imaging (MRI) technique for visualizing and quantifying tissue microstructure based on diffusion. The book discusses the theoretical background underlying DTI and advanced techniques based on higher-order models and multi-shell diffusion imaging. It covers the practical implementation of DTI; derivation of information from DTI data; and a range of clinical applications, including neurosurgical planning and the assessment of brain tumors. Its practical utility is enhanced by decision schemes and a fully annotated DTI brain atlas, including color fractional anisotropy maps and 3D tractography reconstructions of major white matter fiber bundles. Featuring contributions from leading specialists in the field of DTI, Diffusion Tensor Imaging: A Practical Handbook is a valuable resource for radiologists, neuroradiologists, MRI technicians and clinicians.

Geometric Models of Brain White Matter for Microstructure Imaging with Diffusion MRI

Geometric Models of Brain White Matter for Microstructure Imaging with Diffusion MRI  Book
Author : E. Panagiotaki
Publisher : Unknown
Release : 2011
ISBN : 0987650XXX
Language : En, Es, Fr & De

GET BOOK

Book Description :

The research presented in this thesis models the diffusion-weighted MRI signal within brain white matter tissue. We are interested in deriving descriptive microstructure indices such as white matter axon diameter and density from the observed diffusion MRI signal. The motivation is to obtain non-invasive reliable biomarkers for early diagnosis and prognosis of brain development and disease. We use both analytic and numerical models to investigate which properties of the tissue and aspects of the diffusion process affect the diffusion signal we measure. First we develop a numerical method to approximate the tissue structure as closely as possible. We construct three-dimensional meshes, from a stack of confocal microscopy images using the marching cubes algorithm. The experiment demonstrates the technique using a biological phantom (asparagus). We devise an MRI protocol to acquire data from the sample. We use the mesh models as substrates in Monte-Carlo simulations to generate synthetic MRI measurements. To test the feasibility of the method we compare simulated measurements from the three-dimensional mesh with scanner measurements from the same sample and simulated measurements from an extruded mesh and much simpler parametric models. The results show that the three-dimensional mesh model matches the data better than the extruded mesh and the parametric models revealing the sensitivity of the diffusion signal to the microstructure. The second study constructs a taxonomy of analytic multi-compartment models of white matter by combining intra- and extra-axonal compartments from simple models. We devise an imaging protocol that allows diffusion sensitisation parallel and perpendicular to tissue fibres. We use the protocol to acquire data from two fixed rat brains, which allows us to fit, study and evaluate the models. We conclude that models which incorporate non-zero axon radius describe the measurements most accurately. The key observation is a departure of signals in the parallel direction from the two-compartment models, suggesting restriction, most likely from glial cells or binding of water molecules to the membranes. The addition of the third compartment can capture this departure and explain the data. The final study investigates the estimates using in vivo brain diffusion measurements. We adjust the imaging protocol to allow an in vivo MRI acquisition of a rat brain and compare and assess the taxonomy of models. We then select the models that best explain the in vivo data and compare the estimates with those from the ex vivo measurements to identify any discrepancies. The results support the addition of the third compartment model as per the ex vivo findings, however the ranking of the models favours the zero radius intra-axonal compartments.

Computational Diffusion MRI

Computational Diffusion MRI Book
Author : Andrea Fuster,Aurobrata Ghosh,Enrico Kaden,Yogesh Rathi,Marco Reisert
Publisher : Springer
Release : 2016-04-08
ISBN : 3319285882
Language : En, Es, Fr & De

GET BOOK

Book Description :

These Proceedings of the 2015 MICCAI Workshop “Computational Diffusion MRI” offer a snapshot of the current state of the art on a broad range of topics within the highly active and growing field of diffusion MRI. The topics vary from fundamental theoretical work on mathematical modeling, to the development and evaluation of robust algorithms, new computational methods applied to diffusion magnetic resonance imaging data, and applications in neuroscientific studies and clinical practice. Over the last decade interest in diffusion MRI has exploded. The technique provides unique insights into the microstructure of living tissue and enables in-vivo connectivity mapping of the brain. Computational techniques are key to the continued success and development of diffusion MRI and to its widespread transfer into clinical practice. New processing methods are essential for addressing issues at each stage of the diffusion MRI pipeline: acquisition, reconstruction, modeling and model fitting, image processing, fiber tracking, connectivity mapping, visualization, group studies and inference. This volume, which includes both careful mathematical derivations and a wealth of rich, full-color visualizations and biologically or clinically relevant results, offers a valuable starting point for anyone interested in learning about computational diffusion MRI and mathematical methods for mapping brain connectivity, as well as new perspectives and insights on current research challenges for those currently working in the field. It will be of interest to researchers and practitioners in the fields of computer science, MR physics, and applied mathematics.​

Computational Diffusion MRI

Computational Diffusion MRI Book
Author : Noemi Gyori
Publisher : Springer Nature
Release : 2021-12-04
ISBN : 3030730182
Language : En, Es, Fr & De

GET BOOK

Book Description :

Download Computational Diffusion MRI book written by Noemi Gyori, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

The Effect of Tumour Microstructure on Diffusion weighted MRI Measurements

The Effect of Tumour Microstructure on Diffusion weighted MRI Measurements Book
Author : Damien Joseph McHugh
Publisher : Unknown
Release : 2015
ISBN : 0987650XXX
Language : En, Es, Fr & De

GET BOOK

Book Description :

Download The Effect of Tumour Microstructure on Diffusion weighted MRI Measurements book written by Damien Joseph McHugh, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Computational Diffusion MRI

Computational Diffusion MRI Book
Author : Elisenda Bonet-Carne,Francesco Grussu,Lipeng Ning,Farshid Sepehrband,Chantal M. W. Tax
Publisher : Springer
Release : 2019-05-17
ISBN : 303005831X
Language : En, Es, Fr & De

GET BOOK

Book Description :

This volume gathers papers presented at the Workshop on Computational Diffusion MRI (CDMRI’18), which was held under the auspices of the International Conference on Medical Image Computing and Computer Assisted Intervention in Granada, Spain on September 20, 2018. It presents the latest developments in the highly active and rapidly growing field of diffusion MRI. The reader will find papers on a broad range of topics, from the mathematical foundations of the diffusion process and signal generation, to new computational methods and estimation techniques for the in-vivo recovery of microstructural and connectivity features, as well as harmonisation and frontline applications in research and clinical practice. The respective papers constitute invited works from high-profile researchers with a specific focus on three topics that are now gaining momentum within the diffusion MRI community: i) machine learning for diffusion MRI; ii) diffusion MRI outside the brain (e.g. in the placenta); and iii) diffusion MRI for multimodal imaging. The book shares new perspectives on the latest research challenges for those currently working in the field, but also offers a valuable starting point for anyone interested in learning computational techniques in diffusion MRI. It includes rigorous mathematical derivations, a wealth of full-colour visualisations, and clinically relevant results. As such, it will be of interest to researchers and practitioners in the fields of computer science, MRI physics and applied mathematics alike.

Computational Diffusion MRI

Computational Diffusion MRI Book
Author : Suheyla Cetin-Karayumak,Daan Christiaens,Matteo Figini,Pamela Guevara,Noemi Gyori,Vishwesh Nath,Tomasz Pieciak
Publisher : Springer Nature
Release : 2021-09-25
ISBN : 3030876152
Language : En, Es, Fr & De

GET BOOK

Book Description :

This book constitutes the proceedings of the International Workshop on Computational Diffusion MRI, CDMRI 2021, which was held on October 1, 2021, in conjunction with MICCAI 2021. The conference was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic. The 13 full papers included were carefully reviewed and selected for inclusion in the book. The proceedings also contain a paper about the design and scope of the MICCAI Diffusion-Simulated Connectivity Challenge (DiSCo) which was held at CDMRI 2021. The papers were organized in topical sections as follows: acquisition; microstructure modelling; tractography and connectivity; applications and visualization; DiSCo challenge – invited contribution.

In Vivo Quantification of Cardiac Microstructure with Convex Optimized Diffusion Weighted MRI

In Vivo Quantification of Cardiac Microstructure with Convex Optimized Diffusion Weighted MRI Book
Author : Eric Aliotta
Publisher : Unknown
Release : 2017
ISBN : 0987650XXX
Language : En, Es, Fr & De

GET BOOK

Book Description :

Diffusion weighted imaging (DWI) is a powerful quantitative magnetic resonance imaging (MRI) technique that can probe tissues in vivo at the microscopic level and provide insight into cellular microstructural environment. Cardiac DWI has great potential value in its ability to answer open questions regarding myocardial structure, dynamics, and remodeling. Unfortunately, several technical limitations of current DWI techniques make its application in the beating heart very challenging, which leads to erroneous or inconsistent results. Amongst the challenges are an extreme sensitivity to bulk physiological motion, low signal to noise ratios (SNR), long scan times, and geometric image distortions. In this dissertation, these limitations are addressed with novel technical developments applied to the DWI pulse sequence including convex optimized diffusion gradient waveform design and multi-parametric tissue characterization. A brief introduction to Nuclear Magnetic Resonance (NMR) and MRI is provided in Chapter 1. This leads into a description of the fundamental components of a DWI acquisition in Chapter 2 and an overview of the current state of cardiac DWI in Chapter 3. In Chapter 4, a novel DWI strategy called Convex Optimized Diffusion Encoding (CODE) is described. CODE is a mathematical framework that formulates diffusion encoding gradient design as a convex optimization problem and automatically generates motion compensated (MOCO) waveforms that achieve the shortest possible echo times (TE) and thus improve SNR. First and second order moment nulled CODE (CODE-M1M2) permits DWI that is robust to cardiac motion with higher SNR than an existing MOCO technique. First order motion compensated CODE-M1 also improves robustness to cardiac induced motion in liver DWI with higher SNR than M1 nulled bipolar DWI. CODE can also be used for non-motion compensated DWI and improves SNR compared with traditional monopolar DWI in the brain. In Chapter 5 we present a multi-parametric DWI strategy that simultaneously yields maps of the apparent diffusion coefficient (ADC) and T2 relaxation time constant in the heart (T2+ADC). Typically, DWI protocols include multiple acquisitions with a range of diffusion encoding strengths (b-value), but with constant TE to isolate the effect of diffusion of the signal. The joint T2+ADC approach varies both b-value and TE within the acquisition to facilitate estimation of both ADC and T2 relaxation. T2+ADC permits joint reconstruction with no increase in scan time compared with DWI alone and no effect on ADC measurement. In Chapter 6 we use CODE-M1M2 diffusion encoding to perform cardiac diffusion tensor imaging (cDTI) and generate maps of myocardial microstructure in healthy volunteers. cDTI can be used to map myocardial fiber and myolaminar sheetlet orientations, which can contribute to our understanding of ventricular microstructure in health and disease and facilitate sophisticated mechanical models of cardiac dynamics. However, it is important to understand the uncertainty underlying these measurements to inform interpretation and define acquisition limitations. We apply a previously described bootstrap technique to measure the uncertainty in the diffusion tensors derived from CODE-M1M2 cDTI and establish achievable levels of precision in clinically feasible scan times. In Chapter 7 the CODE framework is extended to compensate for the effect of eddy currents, which are a common cause of image distortions in DWI and DTI. Diffusion encoding gradients must be very strong to encode microscopic molecular displacements and these strong gradient pulses induce unwanted eddy currents in conductive MRI hardware components. If not addressed, eddy currents lead to distorted images and corrupted diffusion parameter estimates. We incorporate an eddy current model into the CODE optimization framework to develop eddy current nulled CODE (EN-CODE). EN-CODE accomplishes eddy current nulling with TEs that are comparable to traditional monopolar encoding and much shorter than the established twice refocused spin echo (TRSE) technique for eddy current nulling. The developments described in this dissertation represent an improvement in the flexibility, efficiency, and robustness of diffusion encoding. The CODE framework can also be easily modified to address additional constraints and thus may prove useful in currently unforeseen applications.

Microstructure with Magnetic Resonance

Microstructure with Magnetic Resonance Book
Author : Valerij G. Kiselev,Dmitry S. Novikov
Publisher : Academic Press
Release : 2021-11-15
ISBN : 9780128224694
Language : En, Es, Fr & De

GET BOOK

Book Description :

Microstructure with Magnetic Resonance: Problems and Solutions responds to the challenge of how to see the invisible with magnetic resonance imaging. Technically, the goal is to quantify cellular-level properties of biological tissues and microarchitecture of porous media orders of magnitude below the achievable resolution of MR. While the interest in this area has grown exponentially, current research involves physics outside the scope of standard NMR and MRI textbooks. Microstructure with Magnetic Resonance: Problems and Solutions introduces readers to methods of describing complex media in statistical terms, and covers the effects of complex microenvironments on the MR signal phase, on the transverse relaxation, and on different facets of the diffusion-weighted signal. The book presents the material as a set of problems with detailed solutions, that build on each other, stimulating a hands-on approach to learning. Each chapter begins with a short introduction to the topic, followed by problems, solutions, and a summary of key points. The problems start from the basics, and bring the reader step-by-step to the frontier of current knowledge. The overall focus is on gaining physical insight, by drawing on simple physical analogies and dimensional analysis, which help to reproduce the essence of the results obtained in classical and recent studies. The necessary mathematics is collected in dedicated appendices. With this book the reader will: . Understand the classic and current literature on microstructure mapping with NMR and MRI; . Become familiar with the modern trends in microstructure MR; . Be able to design new experiments using MR based on a solid theoretical foundation. . Explains physics necessary to understand how the microscopic structure of biological tissues and porous media manifests itself in different magnetic resonance contrasts (phase, relaxation, diffusion). . Uses a unique problem/solution structure to provide for efficient learning from the basics to the frontiers of knowledge. . Tested through numerous teaching courses for trainees.

Computational Diffusion MRI

Computational Diffusion MRI Book
Author : Enrico Kaden,Francesco Grussu,Lipeng Ning,Chantal M. W. Tax,Jelle Veraart
Publisher : Springer
Release : 2018-04-02
ISBN : 3319738399
Language : En, Es, Fr & De

GET BOOK

Book Description :

This volume presents the latest developments in the highly active and rapidly growing field of diffusion MRI. The reader will find numerous contributions covering a broad range of topics, from the mathematical foundations of the diffusion process and signal generation, to new computational methods and estimation techniques for the in-vivo recovery of microstructural and connectivity features, as well as frontline applications in neuroscience research and clinical practice. These proceedings contain the papers presented at the 2017 MICCAI Workshop on Computational Diffusion MRI (CDMRI’17) held in Québec, Canada on September 10, 2017, sharing new perspectives on the most recent research challenges for those currently working in the field, but also offering a valuable starting point for anyone interested in learning computational techniques in diffusion MRI. This book includes rigorous mathematical derivations, a large number of rich, full-colour visualisations and clinically relevant results. As such, it will be of interest to researchers and practitioners in the fields of computer science, MRI physics and applied mathematics.

Computational Diffusion MRI

Computational Diffusion MRI Book
Author : Andrea Fuster,Aurobrata Ghosh,Enrico Kaden,Yogesh Rathi,Marco Reisert
Publisher : Springer
Release : 2017-05-11
ISBN : 3319541307
Language : En, Es, Fr & De

GET BOOK

Book Description :

This volume offers a valuable starting point for anyone interested in learning computational diffusion MRI and mathematical methods for brain connectivity, while also sharing new perspectives and insights on the latest research challenges for those currently working in the field. Over the last decade, interest in diffusion MRI has virtually exploded. The technique provides unique insights into the microstructure of living tissue and enables in-vivo connectivity mapping of the brain. Computational techniques are key to the continued success and development of diffusion MRI and to its widespread transfer into the clinic, while new processing methods are essential to addressing issues at each stage of the diffusion MRI pipeline: acquisition, reconstruction, modeling and model fitting, image processing, fiber tracking, connectivity mapping, visualization, group studies and inference. These papers from the 2016 MICCAI Workshop “Computational Diffusion MRI” – which was intended to provide a snapshot of the latest developments within the highly active and growing field of diffusion MR – cover a wide range of topics, from fundamental theoretical work on mathematical modeling, to the development and evaluation of robust algorithms and applications in neuroscientific studies and clinical practice. The contributions include rigorous mathematical derivations, a wealth of rich, full-color visualizations, and biologically or clinically relevant results. As such, they will be of interest to researchers and practitioners in the fields of computer science, MR physics, and applied mathematics.