Download or read book Accelerating Data Acquisition for Advanced Diffusion MRI Models written by Daniel Vincent Olson and published by . This book was released on 2018 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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.

Download or read book Advanced Diffusion Encoding Methods in MRI written by Daniel Topgaard and published by Royal Society of Chemistry. This book was released on 2020-08-06 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: The medical MRI community is by far the largest user of diffusion NMR techniques and this book captures the current surge of methods and provides a primary source to aid adoption in this field. There is a trend to adapting the more advanced diffusion encoding sequences developed by NMR researchers within the fields of porous media, chemical engineering, and colloid science to medical research. Recently published papers indicate great potential for improved diagnosis of the numerous pathological conditions associated with changes of tissue microstructure that are invisible to conventional diffusion MRI. This book disseminates these recent developments to the wider community of MRI researchers and clinicians. The chapters cover the theoretical basis, hardware and pulse sequences, data analysis and validation, and recent applications aimed at promoting further growth in the field. This is a fast moving field and chapters are written by key MRI scientists that have contributed to the successful translation of the advanced diffusion NMR methods to the context of medical MRI, from global locations.

Download or read book Computational Diffusion MRI and Brain Connectivity written by Thomas Schultz and published by Springer Science & Business Media. This book was released on 2014-01-13 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the proceedings from two closely related workshops: Computational Diffusion MRI (CDMRI’13) and Mathematical Methods from Brain Connectivity (MMBC’13), held under the auspices of the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, which took place in Nagoya, Japan, September 2013. Inside, readers will find contributions ranging from mathematical foundations and novel methods for the validation of inferring large-scale connectivity from neuroimaging data to the statistical analysis of the data, accelerated methods for data acquisition, and the most recent developments on mathematical diffusion modeling. This volume offers a valuable starting point for anyone interested in learning computational diffusion MRI and mathematical methods for brain connectivity as well as offers new perspectives and insights on current research challenges for those currently in the field. It will be of interest to researchers and practitioners in computer science, MR physics, and applied mathematics.

Download or read book Heart Mechanics written by El-Sayed H. Ibrahim and published by CRC Press. This book was released on 2017-09-19 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: MRI techniques have been recently introduced for non-invasive qualification of regional myocardial mechanics, which is not achievable with other imaging modalities. Covering more than twenty-three years of developments in MRI techniques for accessing heart mechanics, this book provides a plethora of techniques and concepts that assist readers choose the best technique for their purpose. It reviews research studies and clinical trials that implemented MRI techniques for studying heart mechanics.

Download or read book Diffusion MRI written by Heidi Johansen-Berg and published by Academic Press. This book was released on 2013-11-04 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diffusion MRI remains the most comprehensive reference for understanding this rapidly evolving and powerful technology and is an essential handbook for designing, analyzing, and interpreting diffusion MR experiments. Diffusion imaging provides a unique window on human brain anatomy. This non-invasive technique continues to grow in popularity as a way to study brain pathways that could never before be investigated in vivo. This book covers the fundamental theory of diffusion imaging, discusses its most promising applications to basic and clinical neuroscience, and introduces cutting-edge methodological developments that will shape the field in coming years. Written by leading experts in the field, it places the exciting new results emerging from diffusion imaging in the context of classical anatomical techniques to show where diffusion studies might offer unique insights and where potential limitations lie. Fully revised and updated edition of the first comprehensive reference on a powerful technique in brain imaging Covers all aspects of a diffusion MRI study from acquisition through analysis to interpretation, and from fundamental theory to cutting-edge developments New chapters covering connectomics, advanced diffusion acquisition, artifact removal, and applications to the neonatal brain Provides practical advice on running an experiment Includes discussion of applications in psychiatry, neurology, neurosurgery, and basic neuroscience Full color throughout

Download or read book Advanced Computational Intelligence Methods for Processing Brain Imaging Data written by Kaijian Xia and published by Frontiers Media SA. This book was released on 2022-11-09 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Acceleration of High Angular and Spatial Resolution Diffusion Imaging written by Merry Mani and published by . This book was released on 2014 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Diffusion magnetic resonance imaging (dMRI) is a unique in vivo imaging modality that has the capability to reveal the white matter tissue micro-architecture of the brainches It has propelled our understanding of the structure of the brain, which in turn has helped to understand the functioning of the brain by elucidating the different anatomical connectivity pathways. However, the current diffusion imaging protocols are limited in their ability to generate high resolution images that are crucial in tracing the underlying anatomical connections. In this thesis, a new imaging scheme is developed that can enable the acquisition of high angular and spatial resolution diffusion imaging. High resolution imaging in MRI always comes with the cost of longer scan times and reduced signal-to-noise ratio (SNR). In order to maximize the SNR, we proposed to use multi-shot variable density spiral k-space sampling trajectories for the imaging. In order to reduce the scan time, we proposed to under-sample the combined k-q space of diffusion imaging using an incoherent under-sampling scheme. The recently proposed signal recovery technique known as compressed sensing was employed to recover the images from the under-sampled measurements. By using a sparse complex Gaussian mixture model to depict the diffusion process, the image reconstruction was posed as a sparse recovery problem. Since the complex signal modeling (as opposed to limiting to the real part of the signal) enabled to accurately account for the noise statistics of the k-space data, the proposed joint recovery scheme were able to generate high spatial and angular resolution images from highly under-sampled measurements with high accuracy comparable to that of the fully sampled measurements. With the use of non-Cartesian sampling trajectories, the reconstruction of the images becomes difficult because of the inability to use fast Fourier transforms (FFTs). Conventional gridding reconstructions are unsuitable for the highly under-sampled measurements that we employed. Model based iterative sparse reconstruction schemes are employed in such situations, which are afflicted by long reconstruction times. Combined with the fact that multi-shot acquisitions require motion compensation to reconstruct artifact-free images, the reconstruction time is further lengthened with the accommodation of a motion-compensation scheme. In order to reduce the reconstruction time, we proposed an alternate pipeline for reconstruction. The new scheme involved exploiting the redundancy and smoothness of the sensitivity functions used in the motion-compensated reconstruction. By representing the sensitivity functions in terms of a few basis function derived from a principal component analysis (PCA) bases, the number of non-uniform Fourier transforms to be performed is reduced. The evaluation of non-uniform Fourier transforms were then avoided by exploiting the Toeplitz structure of the product of forward and backward Fourier transforms. Finally, using a fast augmented Lagrangian optimization algorithm, the sparse recovery of diffusion data was accelerated to enable its use in a practical setting"--Pages vi-vii.

Download or read book Computational Diffusion MRI written by Elisenda Bonet-Carne and published by Springer. This book was released on 2019-05-17 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Advanced Neuro MR Techniques and Applications written by In-Young Choi and published by Academic Press. This book was released on 2021-11-17 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced Neuro MR Techniques and Applications gives detailed knowledge of emerging neuro MR techniques and their specific clinical and neuroscience applications, showing their pros and cons over conventional and currently available advanced techniques. The book identifies the best available data acquisition, processing, reconstruction and analysis strategies and methods that can be utilized in clinical and neuroscience research. It is an ideal reference for MR scientists and engineers who develop MR technologies and/or support clinical and neuroscience research and for high-end users who utilize neuro MR techniques in their research, including clinicians, neuroscientists and psychologists. Trainees such as postdoctoral fellows, PhD and MD/PhD students, residents and fellows using or considering the use of neuro MR technologies will also be interested in this book. Presents a complete reference on advanced Neuro MR Techniques and Applications Edited and written by leading researchers in the field Suitable for a broad audience of MR scientists and engineers who develop MR technologies, as well as clinicians, neuroscientists and psychologists who utilize neuro MR techniques in their research

Download or read book Computational Diffusion MRI written by Noemi Gyori and published by Springer Nature. This book was released on 2021-09-29 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers papers presented at the Workshop on Computational Diffusion MRI, CDMRI 2020, held under the auspices of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), which took place virtually on October 8th, 2020, having originally been planned to take place in Lima, Peru. This book presents the latest developments in the highly active and rapidly growing field of diffusion MRI. While offering new perspectives on the most recent research challenges in the field, the selected articles also provide a valuable starting point for anyone interested in learning computational techniques for diffusion MRI. The book includes rigorous mathematical derivations, a large number of rich, full-colour visualizations, and clinically relevant results. As such, it is of interest to researchers and practitioners in the fields of computer science, MRI physics, and applied mathematics. 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 diffusion-relaxometry and frontline applications in research and clinical practice.

Download or read book Toward Advances in Data Acquisition and Analysis for Quantitative Multi contrast Magnetic Resonance Imaging written by Kalina Polet Slavkova and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative magnetic resonance imaging for cancer is an invaluable noninvasive imaging tool with superior tissue contrast and greater specificity for disease than other imaging modalities; however, MRI is costly and lengthy, making it difficult to deploy quantitative imaging techniques alongside existing clinical protocols. Moreover, radiologists require high spatial resolution images for anatomical interpretation, which is not often reconcilable with the need for high temporal resolution in dynamic quantitative imaging schemes. The purpose of this dissertation is to develop novel analysis and acquisition methods that support fast quantitative imaging for substantiating clinical protocols without necessitating significantly longer scan times, thereby providing opportunity for clinical deployment of quantitative MRI protocols. This purpose is achieved through three distinct approaches. First, we take high temporal resolution dynamic contrast-enhanced MRI data from women with locally advanced breast cancer and retrospectively abbreviate the data to varying degrees. We subsequently analyze the full-length and abbreviated datasets with perfusion models and assess the agreement between the quantitative parameters from the full-length and abbreviated analyses, showing that scans can be shortened by up to 58%. Second, using fully sampled variable-flip angle raw data of the brain from healthy volunteers, we retrospectively accelerate the raw data by 8- to 36-fold and apply an untrained deep learning method with physics-based regularization to reconstruct the anatomical images while simultaneously computing the relevant quantitative parameter map. We achieve images with high spatial resolution and quantitative maps that agree strongly with the quantitative information computed from the fully sampled data. Finally, with the purpose of noninvasively describing tumor heterogeneity, we identify three distinct tumor habitats by clustering multiparametric quantitative information from diffusion-weighted and dynamic contrast-enhanced MRI data from a murine model of glioma collected at multiple imaging visits. We subsequently model the growth of the tumor habitats over time with a system of ordinary differential equations, thereby establishing a computationally fast pipeline for noninvasive tumor habitat growth prediction. Overall, these approaches yield novel methods that enable fast acquisition of quantitative MRI data as well as pipelines for retrospective abbreviation and analysis of existing quantitative MRI data

Download or read book Quantitative Magnetic Resonance Imaging written by Nicole Seiberlich and published by Academic Press. This book was released on 2020-11-18 with total page 1094 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative Magnetic Resonance Imaging is a ‘go-to’ reference for methods and applications of quantitative magnetic resonance imaging, with specific sections on Relaxometry, Perfusion, and Diffusion. Each section will start with an explanation of the basic techniques for mapping the tissue property in question, including a description of the challenges that arise when using these basic approaches. For properties which can be measured in multiple ways, each of these basic methods will be described in separate chapters. Following the basics, a chapter in each section presents more advanced and recently proposed techniques for quantitative tissue property mapping, with a concluding chapter on clinical applications. The reader will learn: The basic physics behind tissue property mapping How to implement basic pulse sequences for the quantitative measurement of tissue properties The strengths and limitations to the basic and more rapid methods for mapping the magnetic relaxation properties T1, T2, and T2* The pros and cons for different approaches to mapping perfusion The methods of Diffusion-weighted imaging and how this approach can be used to generate diffusion tensor maps and more complex representations of diffusion How flow, magneto-electric tissue property, fat fraction, exchange, elastography, and temperature mapping are performed How fast imaging approaches including parallel imaging, compressed sensing, and Magnetic Resonance Fingerprinting can be used to accelerate or improve tissue property mapping schemes How tissue property mapping is used clinically in different organs Structured to cater for MRI researchers and graduate students with a wide variety of backgrounds Explains basic methods for quantitatively measuring tissue properties with MRI - including T1, T2, perfusion, diffusion, fat and iron fraction, elastography, flow, susceptibility - enabling the implementation of pulse sequences to perform measurements Shows the limitations of the techniques and explains the challenges to the clinical adoption of these traditional methods, presenting the latest research in rapid quantitative imaging which has the possibility to tackle these challenges Each section contains a chapter explaining the basics of novel ideas for quantitative mapping, such as compressed sensing and Magnetic Resonance Fingerprinting-based approaches

Download or read book DIFFUSION MRI OF THE BREAST E Book written by Mami Iima and published by Elsevier Health Sciences. This book was released on 2022-06-18 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diffusion weighted imaging (DWI) is a key emerging imaging modality for the management of patients with possible breast lesions, and Diffusion MRI of the Breast is the first book to focus on all aspects of DWI in today’s practice. It covers the knowledge necessary to undertake clinical breast DWI, with a thorough review of how DWI is currently used as a breast imaging modality and how breast lesions appear on DWI. Expert clinicians and physicists from around the world share their knowledge and expertise on everything from technical requirements and image analysis to clinical applications of DWI (diagnosis, prognosis, treatment monitoring) with case examples, and upcoming developments in the field (radiomics, AI). Offers an in-depth discussion of DWI’s clinical applications in breast imaging, including the position of DWI with respect to other modalities, the use of DWI in the diagnosis of suspicious lesions with a multiparametric protocol, the use of DWI as an imaging biomarker of prognosis and response prediction, the potential role of DWI for unenhanced breast MR screening, and more. Provides a basic introduction to DWI before discussing a practical approach to clinical interpretation and quality assurance issues. Covers specific challenges and advanced techniques (IVIM, non-Gaussian diffusion, DTI, and other novel techniques), radiomics and artificial intelligence, and different vendor approaches in breast DWI packages. Features more than 500 high-quality images throughout. Explains how DWI could be specifically used to provide information on prognosis and prediction factors. Evaluates the current status of DWI, its potential for the management of breast cancer patients, and possible future developments in the field.

Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2023 written by Hayit Greenspan and published by Springer Nature. This book was released on 2023-09-30 with total page 726 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learning – explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications – abdomen; clinical applications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular; Part VIII: Clinical applications – neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration.

Download or read book Neuroimaging Anatomy Part 1 Brain and Skull An Issue of Neuroimaging Clinics of North America E Book written by Tarik F. Massoud and published by Elsevier Health Sciences. This book was released on 2022-07-19 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this issue of Neuroimaging Clinics, guest editor Dr. Tarik F. Massoud brings his considerable expertise to the topic of Neuroimaging Anatomy, Part 1: Brain and Skull. Anatomical knowledge is critical to reducing both overdiagnosis and misdiagnosis in neuroimaging. This issue is part one of a two-part series on neuroimaging anatomy that focuses on the brain, with each article addressing a specific area. The issue also includes an article on Brain Connectomics: the study of the brain’s structural and functional connections between cells. Contains 13 relevant, practice-oriented topics including anatomy of cerebral cortex, lobes, and the cerebellum; brainstem anatomy; cranial nerves anatomy; brain functional imaging anatomy; imaging of normal brain aging; and more. Provides in-depth clinical reviews on neuroimaging anatomy of the brain and skull, offering actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.

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.