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Statistical Analysis Of Diffusion Tensor Imaging
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Book Synopsis Statistical Analysis of Diffusion Tensor Imaging by : Diwei Zhou
Download or read book Statistical Analysis of Diffusion Tensor Imaging written by Diwei Zhou and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis considers the statistical analysis of diffusion tensor imaging (DTI). DTI is an advanced magnetic resonance imaging (MRI) method that provides a unique insight into biological microstructure \textit{in vivo} by directionally describing the water molecular diffusion. We firstly develop a Bayesian multi-tensor model with reparameterisation for capturing water diffusion at voxels with one or more distinct fibre orientations. Our model substantially alleviates the non-identifiability issue present in the standard multi-tensor model. A Markov chain Monte Carlo (MCMC) algorithm is then developed to study the uncertainty of the model parameters based on the posterior distribution. We apply the Bayesian method to Monte Carlo (MC) simulated datasets as well as a healthy human brain dataset. A region containing crossing fibre bundles is investigated using our multi-tensor model with automatic model selection. A diffusion tensor, a covariance matrix related to the molecular displacement at a particular voxel in the brain, is in the non-Euclidean space of 3x3 positive semidefinite symmetric matrices. We define the sample mean of tensor data to be the Fréchet mean. We carry out the non-Euclidean statistical analysis of diffusion tensor data. The primary focus is on the use of Procrustes size-and-shape space. Comparisons are made with other non-Euclidean techniques, including the log-Euclidean, Riemannian, Cholesky, root Euclidean and power Euclidean methods. The weighted generalised Procrustes analysis has been developed to efficiently interpolate and smooth an arbitrary number of tensors with the flexibility of controlling individual contributions. A new anisotropy measure, Procrustes Anisotropy is defined and compared with other widely used anisotropy measures. All methods are illustrated through synthetic examples as well as white matter tractography of a healthy human brain. Finally, we use Giné’s statistic to design uniformly distributed diffusion gradient direction schemes with different numbers of directions. MC simulation studies are carried out to compare effects of Giné’s and widely used Jones' schemes on tensor estimation. We conclude by discussing potential areas for further research.
Book Synopsis Statistical Analysis of Diffusion Tensor Imaging by : Diwei Zhou
Download or read book Statistical Analysis of Diffusion Tensor Imaging written by Diwei Zhou and published by LAP Lambert Academic Publishing. This book was released on 2011-12 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis considers the statistical analysis of diffusion tensor imaging (DTI). DTI is an advanced magnetic resonance imaging (MRI) method that provides a unique insight into biological microstructure \textit{in vivo} by directionally describing the water molecular diffusion. We firstly develop a Bayesian multi-tensor model with reparameterisation for capturing water diffusion at voxels with one or more distinct fibre orientations. Our model substantially alleviates the non-identifiability issue present in the standard multi-tensor model. A Markov chain Monte Carlo (MCMC) algorithm is then developed to study the uncertainty of the model parameters based on the posterior distribution. We apply the Bayesian method to Monte Carlo (MC) simulated datasets as well as a healthy human brain dataset. A region containing crossing fibre bundles is investigated using our multi-tensor model with automatic model selection. A diffusion tensor, a covariance matrix related to the molecular displacement at a particular voxel in the brain, is in the non-Euclidean space of 3x3 positive semidefinite symmetric matrices. We define the sample mean of tensor data to be the Fréchet mean. We carry out the non-Euclidean statistical analysis of diffusion tensor data. The primary focus is on the use of Procrustes size-and-shape space. Comparisons are made with other non-Euclidean techniques, including the log-Euclidean, Riemannian, Cholesky, root Euclidean and power Euclidean methods. The weighted generalised Procrustes analysis has been developed to efficiently interpolate and smooth an arbitrary number of tensors with the flexibility of controlling individual contributions. A new anisotropy measure, Procrustes Anisotropy is defined and compared with other widely used anisotropy measures. All methods are illustrated through synthetic examples as well as white matter tractography of a healthy human brain. Finally, we use Giné’s statistic to design uniformly distributed diffusion gradient direction schemes with different numbers of directions. MC simulation studies are carried out to compare effects of Giné’s and widely used Jones' schemes on tensor estimation. We conclude by discussing potential areas for further research.
Book Synopsis Diffusion Tensor Imaging by : Wim Van Hecke
Download or read book Diffusion Tensor Imaging written by Wim Van Hecke and published by Springer. This book was released on 2015-12-14 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Nonparametric Statistical Analysis of Diffusion Tensor Imaging Based Fiber Tracking by : Songhe Cai
Download or read book Nonparametric Statistical Analysis of Diffusion Tensor Imaging Based Fiber Tracking written by Songhe Cai and published by . This book was released on 2005 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Diffusion Tensor Imaging by : Bram Stieltjes
Download or read book Diffusion Tensor Imaging written by Bram Stieltjes and published by Springer Science & Business Media. This book was released on 2013-02-14 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diffusion Tensor Imaging (DTI) is a variation of diffusion-weighed imaging. Particularly in the neurosciences, this technique has gained tremendous momentum in the past decade, both from a technical point of view as well as in its applications. DTI is mainly used in neurological diagnosis and psychiatric and neurologic research, e.g. in order to locate brain tumors and depict their invasivity. DTI offers a unique in-vivo insight into the three-dimensional structure of the human central nervous system. While easy interpretation and evaluation is often hampered by the complexity of both the technique and neuroanatomy, this atlas helps you recognize every one of the important structures rapidly and unambiguously. In the introduction, this atlas provides a concise outline of the evolution of diffusion imaging and describes its potential applications. In the core part of the atlas, the neuroanatomically important structures are clearly labeled both on DTI-derived color maps and conventional MRI. Complex fiber architecture is illustrated schematically and described concisely in textboxes directly on the relevant page. In the final part of the atlas, a straightforward, step-by-step approach for the three-dimensional reconstruction of the most prominent fiber structures is given, and potential pitfalls are indicated. The atlas aims at neuroscientists, neuoanatomists, neurologists, psychiatrists, clinical psychologists, physicists, and computer scientists. For advanced users, the atlas may serve as a reference work, while students and scientists are thoroughly introduced in DTI.
Book Synopsis Introduction to Diffusion Tensor Imaging by : Susumu Mori
Download or read book Introduction to Diffusion Tensor Imaging written by Susumu Mori and published by Academic Press. This book was released on 2013-08-02 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concepts behind diffusion tensor imaging (DTI) are commonly difficult to grasp, even for magnetic resonance physicists. To make matters worse, a many more complex higher-order methods have been proposed over the last few years to overcome the now well-known deficiencies of DTI. In Introduction to Diffusion Tensor Imaging: And Higher Order Models, these concepts are explained through extensive use of illustrations rather than equations to help readers gain a more intuitive understanding of the inner workings of these techniques. Emphasis is placed on the interpretation of DTI images and tractography results, the design of experiments, and the types of application studies that can be undertaken. Diffusion MRI is a very active field of research, and theories and techniques are constantly evolving. To make sense of this constantly shifting landscape, there is a need for a textbook that explains the concepts behind how these techniques work in a way that is easy and intuitive to understand—Introduction to Diffusion Tensor Imaging fills this gap. Extensive use of illustrations to explain the concepts of diffusion tensor imaging and related methods Easy to understand, even without a background in physics Includes sections on image interpretation, experimental design, and applications Up-to-date information on more recent higher-order models, which are increasingly being used for clinical applications
Book Synopsis Brain Network Analysis by : Moo K. Chung
Download or read book Brain Network Analysis written by Moo K. Chung and published by Cambridge University Press. This book was released on 2019-06-27 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This coherent mathematical and statistical approach aimed at graduate students incorporates regression and topology as well as graph theory.
Book Synopsis Robust Variability Analysis Using Diffusion Tensor Imaging by : Mustafa Okan Irfanoglu
Download or read book Robust Variability Analysis Using Diffusion Tensor Imaging written by Mustafa Okan Irfanoglu and published by . This book was released on 2011 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, I present new paradigms and an accompanying suite of tools to realize a robust approach to DTI analysis from groupwise variability modeling perspective. The first part of the thesis describes the problems involved in diffusion weighted image and diffusion tensor image processing and why DTI data can not be directly used in a statistical analysis framework performing as a black box. These problems include different types of distortions involved in data acquisitions, unification and assessment of a variety of DTI acquisition protocols, problems involved in diffusion weighted data interpolation, the bias introduced by physiological noise and the data bias. In the second part, these challenges are analyzed in detail and either processing solutions are methodologies to incorporate their effects into statistical frameworks are provided. Efficient and robust algorithms required for multi-data DTI analysis have been developed in the following sections, focusing on spatial alignment of tensor data and computation of tensorial statistics enabling voxel or region-wise variability analysis using DTI data. The complete DTI processing and variability analysis framework developed here was applied to DTI studies for understanding the differences in human brain due to demographic variables.
Book Synopsis Numerical-statistical Methods for an Optimized Analysis of Diffusion Tensor Imaging Data: Applications to Amyotrophic Lateral Sclerosis by : Anna Behler
Download or read book Numerical-statistical Methods for an Optimized Analysis of Diffusion Tensor Imaging Data: Applications to Amyotrophic Lateral Sclerosis written by Anna Behler and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Diffusion Tensor Imaging by : Susanne Heim
Download or read book Statistical Diffusion Tensor Imaging written by Susanne Heim and published by Cuvillier Verlag. This book was released on 2007 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Analysis on Diffusion Tensor Estimation by : Jiajia Yan
Download or read book Statistical Analysis on Diffusion Tensor Estimation written by Jiajia Yan and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in Data Analysis of Diffusion Tensor Imaging by : Cheng Guan Koay
Download or read book Advances in Data Analysis of Diffusion Tensor Imaging written by Cheng Guan Koay and published by . This book was released on 2005 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Diffusion MRI written by Derek K Jones and published by Oxford University Press. This book was released on 2010-11-11 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Advanced analysis of diffusion MRI data by : Xuan Gu
Download or read book Advanced analysis of diffusion MRI data written by Xuan Gu and published by Linköping University Electronic Press. This book was released on 2019-11-19 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diffusion magnetic resonance imaging (diffusion MRI) is a non-invasive imaging modality which can measure diffusion of water molecules, by making the MRI acquisition sensitive to diffusion. Diffusion MRI provides unique possibilities to study structural connectivity of the human brain, e.g. how the white matter connects different parts of the brain. Diffusion MRI enables a range of tools that permit qualitative and quantitative assessments of many neurological disorders, such as stroke and Parkinson. This thesis introduces novel methods for diffusion MRI data analysis. Prior to estimating a diffusion model in each location (voxel) of the brain, the diffusion data needs to be preprocessed to correct for geometric distortions and head motion. A deep learning approach to synthesize diffusion scalar maps from a T1-weighted MR image is proposed, and it is shown that the distortion-free synthesized images can be used for distortion correction. An evaluation, involving both simulated data and real data, of six methods for susceptibility distortion correction is also presented in this thesis. A common problem in diffusion MRI is to estimate the uncertainty of a diffusion model. An empirical evaluation of tractography, a technique that permits reconstruction of white matter pathways in the human brain, is presented in this thesis. The evaluation is based on analyzing 32 diffusion datasets from a single healthy subject, to study how reliable tractography is. In most cases only a single dataset is available for each subject. This thesis presents methods based on frequentistic (bootstrap) as well as Bayesian inference, which can provide uncertainty estimates when only a single dataset is available. These uncertainty measures can then, for example, be used in a group analysis to downweight subjects with a higher uncertainty.
Book Synopsis Visualization and Processing of Tensor Fields by : Joachim Weickert
Download or read book Visualization and Processing of Tensor Fields written by Joachim Weickert and published by Springer Science & Business Media. This book was released on 2007-06-25 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Matrix-valued data sets – so-called second order tensor fields – have gained significant importance in scientific visualization and image processing due to recent developments such as diffusion tensor imaging. This book is the first edited volume that presents the state of the art in the visualization and processing of tensor fields. It contains some longer chapters dedicated to surveys and tutorials of specific topics, as well as a great deal of original work by leading experts that has not been published before. It serves as an overview for the inquiring scientist, as a basic foundation for developers and practitioners, and as as a textbook for specialized classes and seminars for graduate and doctoral students.
Book Synopsis Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2004 by : Christian Barillot
Download or read book Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2004 written by Christian Barillot and published by Springer. This book was released on 2004-09-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 7th International Conference on Medical Imaging and Computer Assisted Intervention, MICCAI 2004, was held in Saint-Malo, Brittany, France at the “Palais du Grand Large” conference center, September 26–29, 2004. The p- posaltohostMICCAI2004wasstronglyencouragedandsupportedbyIRISA, Rennes. IRISA is a publicly funded national research laboratory with a sta? of 370,including150full-timeresearchscientistsorteachingresearchscientistsand 115 postgraduate students. INRIA, the CNRS, and the University of Rennes 1 are all partners in this mixed research unit, and all three organizations were helpful in supporting MICCAI. MICCAI has become a premier international conference with in-depth - pers on the multidisciplinary ?elds of medical image computing, comput- assisted intervention and medical robotics. The conference brings together cl- icians, biological scientists, computer scientists, engineers, physicists and other researchers and o?ers them a forum to exchange ideas in these exciting and rapidly growing ?elds. The impact of MICCAI increases each year and the quality and quantity of submitted papers this year was very impressive. We received a record 516 full submissions (8 pages in length) and 101 short communications (2 pages) from 36 di?erent countries and 5 continents (see ?gures below). All submissions were reviewed by up to 4 external reviewers from the Scienti?c Review C- mittee and a primary reviewer from the Program Committee. All reviews were then considered by the MICCAI 2004 Program Committee, resulting in the acceptance of 235 full papers and 33 short communications.
Book Synopsis Neuroimaging in Developmental Clinical Neuroscience by : Judith M. Rumsey
Download or read book Neuroimaging in Developmental Clinical Neuroscience written by Judith M. Rumsey and published by Cambridge University Press. This book was released on 2009-02-19 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern neuroimaging offers tremendous opportunities for gaining insights into normative development and a wide array of developmental neuropsychiatric disorders. Focusing on ontogeny, this text covers basic processes involved in both healthy and atypical maturation, and also addresses the range of neuroimaging techniques most widely used for studying children. This book will enable you to understand normative structural and functional brain maturation and the mechanisms underlying basic developmental processes; become familiar with current knowledge and hypotheses concerning the neural bases of developmental neuropsychiatric disorders; and learn about neuroimaging techniques, including their unique strengths and limitations. Coverage includes normal developmental processes, atypical processing in developmental neuropsychiatric disorders, ethical issues, neuroimaging techniques and their integration with psychopharmacologic and molecular genetic research approaches, and future directions. This comprehensive volume is an essential resource for neurologists, neuropsychologists, psychiatrists, pediatricians, and radiologists concerned with normal development and developmental neuropsychiatric disorders.
