This research addresses the problem of acquiring a time series of magnetic resonance images with both high spatial and temporal resolutions. Specifically, we systematically investigate the advantages and limitations of reduced-encoding imaging using a priori constraints. This study reveals that if the available a priori information is a reference image, direct use of this information to 'optimize' data acquisition using the existing wavelet transform or singular value decomposition schemes can undermine the capability to detect new image features. However, proper incorporation of the a priori information in the image reconstruction step can significantly reduce the resolution loss associated with reduced-encoding. For Fourier encoded data, we have shown that the Generalized-Series (GS) model is an effective mathematical framework for carrying out the constrained reconstruction step. Several techniques are proposed in this dissertation to improve the basis functions of the GS model by introducing dynamic information. The two reference reduced-encoding imaging by generalized-series reconstruction (TRIGR) method suppresses background information through the use of a second high resolution reference image. A second technique injects information from the dynamic data into the GS basis functions, as opposed to deriving them solely from the reference information. These techniques allow the GS basis functions to more accurately represent the areas of dynamic change. Finally, motion that occurs between the acquisition of the reference and dynamic data sets can render the reference information useless as a constraint for image reconstruction. A motion compensation method is proposed which uses a similarity norm to accurately detect the motion in spite of contrast changes and the low resolution nature of the dynamic data.

This text equips radiologists with a firm working knowledge of the physical principles underlying cardiovascular MR image generation. Emphasis is on practical applications of MR physics in customizing and optimizing imaging sequences and protocols and minimizing artifacts. Section I covers basic principles of MR physics and includes a chapter on safety. Section II applies these principles to vascular imaging, including gadolinium-enhanced MR angiography. Section III examines various techniques and applications of cardiac MR imaging. Each chapter includes boxed Key Concepts, Challenging Questions, and Review Questions, and many chapters include sample protocols. More than 400 drawings and scans complement the text.

Based on research and clinical trials, this book details the latest research in magnetic resonance imaging (MRI) tagging technology related to heart mechanics. It covers clinical applications and examines future trends, providing a guide for future uses of MRI technology for studying heart mechanics.

This book constitutes the refereed proceedings of 11 IPPS/SPDP '98 Workshops held in conjunction with the 13th International Parallel Processing Symposium and the 10th Symposium on Parallel and Distributed Processing in San Juan, Puerto Rico, USA in April 1999. The 126 revised papers presented were carefully selected from a wealth of papers submitted. The papers are organised in topical sections on biologically inspired solutions to parallel processing problems: High-Level Parallel Programming Models and Supportive Environments; Biologically Inspired Solutions to Parallel Processing; Parallel and Distributed Real-Time Systems; Run-Time Systems for Parallel Programming; Reconfigurable Architectures; Java for Parallel and Distributed Computing; Optics and Computer Science; Solving Irregularly Structured Problems in Parallel; Personal Computer Based Workstation Networks; Formal Methods for Parallel Programming; Embedded HPC Systems and Applications.