This work explores if combining information from multiple Magnetic Resonance Imaging (MRI) modalities provides improved interpretation of brain biological architecture as each MR modality can reveal different characteristics of underlying anatomical structures. Structural MRI provides a means for high-resolution quantitative study of brain morphometry. Diffusion-weighted MR imaging (DWI) allows for low-resolution modeling of diffusivity properties of water molecules. Structural and diffusion-weighted MRI modalities are commonly used for monitoring the biological architecture of the brain in normal development or neurodegenerative disease processes. Structural MRI provides an overall map of brain tissue organization that is useful for identifying distinct anatomical boundaries that define gross organization of the brain. DWI models provide a reflection of the micro-structure of white matter (WM), thereby providing insightful information for measuring localized tissue properties or for generating maps of brain connectivity. Multispectral information from different structural MR modalities can lead to better delineation of anatomical boundaries, but careful considerations should be taken to deal with increased partial volume effects (PVE) when input modalities are provided in different spatial resolutions. Interpretation of diffusion-weighted MRI is strongly limited by its relatively low spatial resolution. PVE's are an inherent consequence of the limited spatial resolution in low-resolution images like DWI. This work develops novel methods to enhance tissue classification by addressing challenges of partial volume effects encountered from multi-modal data that are provided in different spatial resolutions. Additionally, this project addresses PVE in low-resolution DWI scans by introducing a novel super-resolution reconstruction approach that uses prior information from multi-modal structural MR images provided in higher spatial resolution.

This book discusses the modeling and analysis of magnetic resonance imaging (MRI) data acquired from the human brain. The data processing pipelines described rely on R. The book is intended for readers from two communities: Statisticians who are interested in neuroimaging and looking for an introduction to the acquired data and typical scientific problems in the field; and neuroimaging students wanting to learn about the statistical modeling and analysis of MRI data. Offering a practical introduction to the field, the book focuses on those problems in data analysis for which implementations within R are available. It also includes fully worked examples and as such serves as a tutorial on MRI analysis with R, from which the readers can derive their own data processing scripts. The book starts with a short introduction to MRI and then examines the process of reading and writing common neuroimaging data formats to and from the R session. The main chapters cover three common MR imaging modalities and their data modeling and analysis problems: functional MRI, diffusion MRI, and Multi-Parameter Mapping. The book concludes with extended appendices providing details of the non-parametric statistics used and the resources for R and MRI data.The book also addresses the issues of reproducibility and topics like data organization and description, as well as open data and open science. It relies solely on a dynamic report generation with knitr and uses neuroimaging data publicly available in data repositories. The PDF was created executing the R code in the chunks and then running LaTeX, which means that almost all figures, numbers, and results were generated while producing the PDF from the sources.

A unique review of the essential topographical anatomy of the brain from an MRI perspective, correlating high-quality anatomical plates with high-resolution MRI images. The book includes a historical review of brain mapping and an analysis of the essential reference planes used. It provides a detailed review of the sulcal and the gyral anatomy of the human cortex, guiding readers through an interpretation of the individual brain atlas provided by high-resolution MRI. The relationship between brain structure and function is approached in a topographical fashion with an analysis of the necessary imaging methodology and displayed anatomy. An extensive coronal atlas rounds off the book.

This book discusses modelling and analysis of Magnetic Resonance Imaging (MRI) data of the human brain. For the data processing pipelines we rely on R, the software environment for statistical computing and graphics. The book is intended for readers from two communities: Statisticians, who are interested in neuroimaging and look for an introduction to the acquired data and typical scientific problems in the field and neuroimaging students, who want to learn about the statistical modeling and analysis of MRI data. Being a practical introduction, the book focuses on those problems in data analysis for which implementations within R are available. By providing full worked-out examples the book thus serves as a tutorial for MRI analysis with R, from which the reader can derive its own data processing scripts. The book starts with a short introduction into MRI. The next chapter considers the process of reading and writing common neuroimaging data formats to and from the R session. The main chapters then cover four common MR imaging modalities and their data modeling and analysis problems: functional MRI, diffusion MRI, Multi-Parameter Mapping and Inversion Recovery MRI. The book concludes with extended Appendices on details of the utilize non-parametric statistics and on resources for R and MRI data. The book also addresses the issues of reproducibility and topics like data organization and description, open data and open science. It completely relies on a dynamic report generation with knitr: The books R-code and intermediate results are available for reproducibility of the examples.

An Atlas for the 21st Century The most precise, cutting-edge images of normal cerebral anatomy available today are the centerpiece of this spectacular atlas for clinicians, trainees, and students in the neurologically-based medical and non-medical specialties. Truly an ìatlas for the 21st century,î this comprehensive visual reference presents a detailed overview of cerebral anatomy acquired through the use of multiple imaging modalities including advanced techniques that allow visualization of structures not possible with conventional MRI or CT. Beautiful color illustrations using 3-D modeling techniques based upon 3D MR volume data sets further enhances understanding of cerebral anatomy and spatial relationships. The anatomy in these color illustrations mirror the black and white anatomic MR images presented in this atlas. Written by two neuroradiologists and an anatomist who are also prominent educators, along with more than a dozen contributors, the atlas begins with a brief introduction to the development, organization, and function of the human brain. What follows is more than 1,000 meticulously presented and labelled images acquired with the full complement of standard and advanced modalities currently used to visualize the human brain and adjacent structuresóincluding MRI, CT, diffusion tensor imaging (DTI) with tractography, functional MRI, CTA, CTV, MRA, MRV, conventional 2-D catheter angiography, 3-D rotational catheter angiography, MR spectroscopy, and ultrasound of the neonatal brain. The vast array of data that these modes of imaging provide offers a wider window into the brain and allows the reader a unique way to integrate the complex anatomy presented. Ultimately the improved understanding you can acquire using this atlas can enhance clinical understanding and have a positive impact on patient care. Additionally, various anatomic structures can be viewed from modality to modality and from multiple planes. This state-of-the-art atlas provides a single source reference, which allows the interested reader ease of use, cross-referencing, and the ability to visualize high-resolution images with detailed labeling. It will serve as an authoritative learning tool in the classroom, and as an invaluable practical resource at the workstation or in the office or clinic. Key Features: Provides detailed views of anatomic structures within and around the human brain utilizing over 1,000 high quality images across a broad range of imaging modalities Contains extensively labeled images of all regions of the brain and adjacent areas that can be compared and contrasted across modalities Includes specially created color illustrations using computer 3-D modeling techniques to aid in identifying structures and understanding relationships Goes beyond a typical brain atlas with detailed imaging of skull base, calvaria, facial skeleton, temporal bones, paranasal sinuses, and orbits Serves as an authoritative learning tool for students and trainees and practical reference for clinicians in multiple specialties

With the advances in image guided surgery for cancer treatment, the role of image segmentation and registration has become very critical. The central engine of any image guided surgery product is its ability to quantify the organ or segment the organ whether it is a magnetic resonance imaging (MRI) and computed tomography (CT), X-ray, PET, SPECT, Ultrasound, and Molecular imaging modality. Sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures present in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning system designs. The focus of this book in towards the state of the art techniques in the area of image segmentation and registration.

The brainstem is one of the least understood parts of the human brain despite its prime importance for the maintenance of basic vital functions. Owing to its role as a relay station between spinal cord, cerebellum and neocortex, the brainstem contains vital nodes of all functional systems in the central nervous system, including the visual, auditory, gustatory, vestibular, somatic and visceral senses, and the somatomotor as well as autonomic nervous systems. While the brainstem has been extensively studied in animals using invasive methods, human studies remain scarce. Magnetic resonance imaging (MRI) as a non-invasive and widely available method is one possibility to access the brainstem in humans and measure its structure as well as function. The close vicinity of the brainstem to large arteries and ventricles and the small size of the anatomical structures, however, place high demands on imaging as well as data analysis methods. Nevertheless, the field of brainstem-(f)MRI has significantly advanced in the past few years, largely due to the development of several new tools that facilitate studying this critical part of the human brain. Within this scope, the goal of this Research Topic is to compile work representing the state of the art in functional and structural MRI of the human brainstem.