This book offers a unique guide to the entire chain of biomedical imaging, explaining how image formation is done, and how the most appropriate algorithms are used to address demands and diagnoses. It is an exceptional tool for radiologists, research scientists, senior undergraduate and graduate students in health sciences and engineering, and university professors.

This volume details promising analytical and numerical techniques for solving challenging biomedical imaging problems, which trigger the investigation of interesting issues in various branches of mathematics.

Nanotechnology for Biomedical Imaging and Diagnostics: From Nanoparticle Design to Clinical Applications reflects upon the increasing role of nanomaterials in biological and medical imaging, presenting a thorough description of current research as well as future directions. With contributions from experts in nanotechnology and imaging from academia, industry, and healthcare, this book provides a comprehensive coverage of the field, ranging from the architectural design of nanomaterials to their broad imaging applications in medicine. Grouped into three sections, the book: Elucidates all major aspects of nanotechnology and bioimaging Provides comprehensive coverage of the field, ranging from the architectural design of nanomaterials to their broad imaging applications in medicine Written by well-recognized experts in academia, industry, and healthcare, will be an excellence source of reference With a multidisciplinary approach and a balance of research and diagnostic topics, this book will appeal to students, scientiests, and healthcare professionals alike

Most books discuss general and broad topics regarding molecular imagings. However, Ultrasmall Lanthanide Oxide Nanoparticles for Biomedical Imaging and Therapy, will mainly focus on lanthanide oxide nanoparticles for molecular imaging and therapeutics. Multi-modal imaging capabilities will discussed, along with up-converting FI by using lanthanide oxide nanoparticles. The synthesis will cover polyol synthesis of lanthanide oxide nanoparticles, Surface coatings with biocompatible and hydrophilic ligands will be discussed and TEM images and dynamic light scattering (DLS) patterns will be provided. Various techniques which are generally used in analyzing the synthesized surface coated nanoparticles will be explored and this section will also cover FT, IR analysis, XRD analysis, SQUID analysis, cytotoxicity measurements and proton relaxivity measurements. In vivo MR images, CT images, fluorescence images will be provided and Therapeutic application of gadolinium oxide nanoparticles will be discussed. Finally, future perpectives will be discussed. That is, present status and future works needed for clinical applications of lanthanide oxide nanoparticles to molecular imagings will be discussed. - Synthesis will be discussed in detail - General characterizations of nanoparticles before in vivo applications will be discussed - The book will cover all possible applications of lanthanide oxide nanoparticles to molecular imagings such as MRI, CT, FI as well as therapeutics

Biomedical imaging is becoming an indispensable branch within bioengineering. This research field has recently expanded due to the requirement of high-level medical diagnostics and rapid development of interdisciplinary modern technologies. This book is designed to present the most recent advances in instrumentation, methods, and image processing as well as clinical applications in important areas of biomedical imaging. It provides broad coverage of the field of biomedical imaging, with particular attention to an engineering viewpoint. The goal of the book is to provide a wide-ranging forum in the biomedical imaging field that integrates interdisciplinary research and development of interest to scientists, engineers, teachers, students, and clinical providers.

A comprehensive guide to understanding and interpreting digital images in medical and functional applications Biomedical Image Understanding focuses on image understanding and semantic interpretation, with clear introductions to related concepts, in-depth theoretical analysis, and detailed descriptions of important biomedical applications. It covers image processing, image filtering, enhancement, de-noising, restoration, and reconstruction; image segmentation and feature extraction; registration; clustering, pattern classification, and data fusion. With contributions from experts in China, France, Italy, Japan, Singapore, the United Kingdom, and the United States, Biomedical Image Understanding: Addresses motion tracking and knowledge-based systems, two areas which are not covered extensively elsewhere in a biomedical context Describes important clinical applications, such as virtual colonoscopy, ocular disease diagnosis, and liver tumor detection Contains twelve self-contained chapters, each with an introduction to basic concepts, principles, and methods, and a case study or application With over 150 diagrams and illustrations, this bookis an essential resource for the reader interested in rapidly advancing research and applications in biomedical image understanding.

Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. Including interdisciplinary examples and a step-by-step background of deep learning, this book provides insight into the future of biomedical image reconstruction with clinical studies and mathematical theory.

Computers have become an integral part of medical imaging systems and are used for everything from data acquisition and image generation to image display and analysis. As the scope and complexity of imaging technology steadily increase, more advanced techniques are required to solve the emerging challenges. Biomedical Image Analysis demonstr

As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires modality-specific algorithmic treatment. In recent years, substantial progress has been made to biomedical image segmentation. Biomedical image segmentation is characterized by several specific factors. This book presents an overview of the advanced segmentation algorithms and their applications.