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Based on the analytical methods and the computer programs presented in this book, all that may be needed to perform MRI tissue diagnosis is the availability of relaxometric data and simple computer program proficiency. These programs are easy to use, highly interactive and the data processing is fast and unambiguous. Laboratories (with or without sophisticated facilities) can perform computational magnetic resonance diagnosis with only T1 and T2 relaxation data. The results have motivated the use of data to produce data-driven predictions required for machine learning, artificial intelligence (AI) and deep learning for multidisciplinary and interdisciplinary research. Consequently, this book is intended to be very useful for students, scientists, engineers, the medical personnel and researchers who are interested in developing new concepts for deeper appreciation of computational magnetic resonance imaging for medical diagnosis, prognosis, therapy and management of tissue diseases.
This book describes the basics, the challenges and the limitations of state of the art brain tumor imaging and examines in detail its impact on diagnosis and treatment monitoring. It opens with an introduction to the clinically relevant physical principles of brain imaging. Since MR methodology plays a crucial role in brain imaging, the fundamental aspects of MR spectroscopy, MR perfusion and diffusion-weighted MR methods are described, focusing on the specific demands of brain tumor imaging. The potential and the limits of new imaging methodology are carefully addressed and compared to conventional MR imaging. In the main part of the book, the most important imaging criteria for the differential diagnosis of solid and necrotic brain tumors are delineated and illustrated in examples. A closing section is devoted to the use of MR methods for the monitoring of brain tumor therapy. The book is intended for radiologists, neurologists, neurosurgeons, oncologists and other scientists in the biomedical field with an interest in neuro-oncology.
Radioisotope-based molecular imaging probes provide unprecedented insight into biochemistry and function involved in both normal and disease states of living systems, with unbiased in vivo measurement of regional radiotracer activities offering very high specificity and sensitivity. No other molecular imaging technology including functional magnetic resonance imaging (fMRI) can provide such high sensitivity and specificity at a tracer level. The applications of this technology can be very broad ranging from drug development, pharmacokinetics, clinical investigations, and finally to routine diagnostics in radiology. The design and the development of radiopharmaceuticals for molecular imaging studies using PET/MicroPET or SPECT/MicroSPECT are a unique challenge. This book is intended for a broad audience and written with the main purpose of educating the reader on various aspects including potential clinical utility, limitations of drug development, and regulatory compliance and approvals.
The field of molecular imaging of living subjects have evolved considerably and have seen spectacular advances in chemistry, engineering and biomedical applications. This textbook was designed to fill the need for an authoritative source for this multi-disciplinary field. We have been fortunate to recruit over 80 leading authors contributing 75 individual chapters. Given the multidisciplinary nature of the field, the book is broken into six different sections: "Molecular Imaging technologies", "Chemistry", "Molecular Imaging in Cell and Molecular Biology", "Applications of Molecular Imaging", "Molecular Imaging in Drug Evaluation" with the final section comprised of chapters on computation, bioinformatics and modeling. The organization of this large amount of information is logical and strives to avoid redundancies among chapters. It encourages the use of figures to illustrate concepts and to provide numerous molecular imaging examples.
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
With an incredible 2400 illustrations, and written by a multitude of international experts, this book provides a comprehensive overview of both the physics and the clinical applications of MRI, including practical guidelines for imaging. The authors define the importance of MRI in the diagnosis of several disease groups in comparison or combination with other methods. Chapters dealing with basic principles of MRI, MR spectroscopy (MRS), interventional MRI and functional MRI (fMRI) illustrate the broad range of applications for MRI. Both standard and cutting-edge applications of MRI are included. Material on molecular imaging and nanotechnology give glimpses into the future of the field.
Currently there is no shortage of challenges and opportunities for PET instrumentation and quantitative imaging techniques. Molecular imaging technologies are leading to a revolutionary paradigm shift in health care and clinical practice. This issue reviews recent advances in PET instrumentation as well as volume correction strategies and strategies for motion tracking and correction, scatter compensation techniques, and attenuation correction techniques.
Over the past decade, fluorine (19F) magnetic resonance imaging (MRI) has garnered significant scientific interest in the biomedical research community owing to the unique properties of fluorinated materials and the 19F nucleus. Fluorine has an intrinsically sensitive nucleus for MRI. There is negligible endogenous 19F in the body and thus there is no background signal. Fluorine-containing compounds are ideal tracer labels for a wide variety of MRI applications. Moreover, the chemical shift and nuclear relaxation rate can be made responsive to physiology via creative molecular design. This book is an interdisciplinary compendium that details cutting-edge science and medical research in the emerging field of 19F MRI. Edited by Ulrich Flögel and Eric Ahrens, two prominent MRI researchers, this book will appeal to investigators involved in MRI, biomedicine, immunology, pharmacology, probe chemistry, and imaging physics.
BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.