This introduction to medical imaging introduces all of the major medical imaging techniques in wide use in both medical practice and medical research, including Computed Tomography, Ultrasound, Positron Emission Tomography, Single Photon Emission Tomography and Magnetic Resonance Imaging. Principles of Medical Imaging for Engineers introduces fundamental concepts related to why we image and what we are seeking to achieve to get good images, such as the meaning of 'contrast' in the context of medical imaging. This introductory text separates the principles by which 'signals' are generated and the subsequent 'reconstruction' processes, to help illustrate that these are separate concepts and also highlight areas in which apparently different medical imaging methods share common theoretical principles. Exercises are provided in every chapter, so the student reader can test their knowledge and check against worked solutions and examples. The text considers firstly the underlying physical principles by which information about tissues within the body can be extracted in the form of signals, considering the major principles used: transmission, reflection, emission and resonance. Then, it goes on to explain how these signals can be converted into images, i.e., full 3D volumes, where appropriate showing how common methods of 'reconstruction' are shared by some imaging methods despite relying on different physics to generate the 'signals'. Finally, it examines how medical imaging can be used to generate more than just pictures, but genuine quantitative measurements, and increasingly measurements of physiological processes, at every point within the 3D volume by methods such as the use of tracers and advanced dynamic acquisitions. Principles of Medical Imaging for Engineers will be of use to engineering and physical science students and graduate students with an interest in biomedical engineering, and to their lecturers.

This book provides an introduction to qualitative and quantitative aspects of human physiology. It examines biological and physiological processes and phenomena, including a selection of mathematical models, showing how physiological problems can be mathematically formulated and studied. It also illustrates how a wide range of engineering and physics topics, such as electronics, fluid dynamics, solid mechanics and control theory can be used to describe and understand physiological processes and systems. Throughout the text, there are introductions to measuring and quantifying physiological processes using both signaling and imaging technologies. This new edition includes updated material on pathophysiology, metabolism and the TCA cycle, as well as more advanced worked examples. This book describes the basic structure and models of cellular systems, the structure and function of the cardiovascular system, and the electrical and mechanical activity of the heart, and provides an overview of the structure and function of the respiratory and nervous systems. It also includes an introduction to the basic concepts and applications of reaction kinetics, pharmacokinetic modelling and tracer kinetics. It appeals to final year biomedical engineering undergraduates and graduates alike, as well as to practising engineers new to the fields of bioengineering or medical physics.

This book provides an introduction to qualitative and quantitative aspects of human physiology. It examines biological and physiological processes and phenomena, including a selection of mathematical models, showing how physiological problems can be mathematically formulated and studied. It also illustrates how a wide range of engineering and physics topics, such as electronics, fluid dynamics, solid mechanics and control theory can be used to describe and understand physiological processes and systems. Throughout the text, there are introductions to measuring and quantifying physiological processes using both signaling and imaging technologies. This new edition includes updated material on pathophysiology, metabolism and the TCA cycle, as well as more advanced worked examples. This book describes the basic structure and models of cellular systems, the structure and function of the cardiovascular system, and the electrical and mechanical activity of the heart, and provides an overview of the structure and function of the respiratory and nervous systems. It also includes an introduction to the basic concepts and applications of reaction kinetics, pharmacokinetic modelling and tracer kinetics. It appeals to final year biomedical engineering undergraduates and graduates alike, as well as to practising engineers new to the fields of bioengineering or medical physics.

This introduction to medical imaging introduces all of the major medical imaging techniques in wide use in both medical practice and medical research, including Computed Tomography, Ultrasound, Positron Emission Tomography, Single Photon Emission Tomography and Magnetic Resonance Imaging. Principles of Medical Imaging for Engineers introduces fundamental concepts related to why we image and what we are seeking to achieve to get good images, such as the meaning of 'contrast' in the context of medical imaging. This introductory text separates the principles by which 'signals' are generated and the subsequent 'reconstruction' processes, to help illustrate that these are separate concepts and also highlight areas in which apparently different medical imaging methods share common theoretical principles. Exercises are provided in every chapter, so the student reader can test their knowledge and check against worked solutions and examples. The text considers firstly the underlying physical principles by which information about tissues within the body can be extracted in the form of signals, considering the major principles used: transmission, reflection, emission and resonance. Then, it goes on to explain how these signals can be converted into images, i.e., full 3D volumes, where appropriate showing how common methods of 'reconstruction' are shared by some imaging methods despite relying on different physics to generate the 'signals'. Finally, it examines how medical imaging can be used to generate more than just pictures, but genuine quantitative measurements, and increasingly measurements of physiological processes, at every point within the 3D volume by methods such as the use of tracers and advanced dynamic acquisitions. Principles of Medical Imaging for Engineers will be of use to engineering and physical science students and graduate students with an interest in biomedical engineering, and to their lecturers.

MRI has emerged as a powerful way of studying in-vivo brain structure and function in both healthy and disease states. Whilst new researchers may be able to call upon advice and support for acquisition from operators, radiologists and technicians, it is more challenging to obtain an understanding of the principles of analysing neuroimaging data. This is crucial for choosing acquisition parameters, designing and performing appropriate experiments, and correctly interpreting the results. This primer gives a general and accessible introduction to the wide array of MRI-based neuroimaging methods that are used in research. Supplemented with online datasets and examples to enable the reader to obtain hands-on experience working with real data, it provides a practical and approachable introduction for those new to the neuroimaging field. The text also covers the fundamentals of what different MRI modalities measure, what artifacts commonly occur, the essentials of the analysis, and common 'pipelines' including brain extraction, registration and segmentation. As it does not require any background knowledge beyond high-school mathematics and physics, this primer is essential reading for anyone wanting to work in neuroimaging or grasp the results coming from this rapidly expanding field. The Oxford Neuroimaging Primers are short texts aimed at new researchers or advanced undergraduates from the biological, medical or physical sciences. They are intended to provide a broad understanding of the ways in which neuroimaging data can be analyzed and how that relates to acquisition and interpretation. Each primer has been written so that it is a stand-alone introduction to a particular area of neuroimaging, and the primers also work together to provide a comprehensive foundation for this increasingly influential field.

Arterial Spin Labeling (ASL) is an increasingly popular tool to study the brain. What sets it apart from other neuroimaging methods is the combination of quantitative measurements of a physiologically well-defined process, namely perfusion, and a completely non-invasive acquisition methodology. Cerebral perfusion is a critical component to brain health, as it is the primary means to deliver nutrients to support brain function as well as clearing waste products. Hence it is a useful quantity to study in disease where changes in perfusion can indicate regions of the brain that are pathological. Likewise changes in perfusion can be indicative of greater demand for nutrients, such as might be required in response to an increase in neuronal activity. With the advent of a consensus by the ASL community on good practice and a recommendation on robust methods for ASL data collection, more and more researchers are now able to access and use ASL. Despite the technological advances, ASL remains a technique with a low signal to noise ratio. This makes the wise choice of the appropriate analysis methods more important. The aim of this primer is to equip someone new to the field of perfusion imaging and ASL with the knowledge not only to make good choices about ASL acquisition and analysis, but also to understand what choices they are making and why. Examples of analysis applied to real data are given throughout the text and instructions on how to reproduce the analyses are illustrated on the primer website. Written to provide a stand-alone introduction to perfusion qualification using ASL, this primer also works with other texts in the Oxford Neuroimaging Primers series to provide a comprehensive overview of the increasingly influential field of neuroimaging.