Michael Chappell

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About Michael Chappell
Michael is an Associate Professor of Engineering Science at the Institute of Biomedical Engineering (IBME), Department of Engineering Science, University of Oxford.
Michael heads the Quantitative Biomedical Inference group that brings together inference techniques from information engineering with mathematical models of physics and physiology to estimate quantitative information for biomedical and especially clinical applications. His main interest is in medical imaging of metabolism and haemodynamics.
Michael read Engineering Science in Oxford at undergraduate level, specializing in information engineering topics and completing a project on the detection of landmines. He stayed to completed a doctorate in SCUBA diving, primarily using mathematical models to explore the growth of bubbles from dissolved gases under decompression in the body - the resulting sickness is commonly referred to as 'the bends'. Finally he found his way into Magnetic Resonance Imaging and now develops ways to measure blood flow and pH in the body with applications in stroke, cancer and dementia.
Michael is a series editor for the Oxford Neuroimaging Primers and an author of two of the primers: Introduction to Neuroimaging Analysis & Introduction to Perfusion Quantification using Arterial Spin Labelling. He has also authored textbooks on biomedical engineering topics - introducing physiology and medical imaging to engineers and other physical science students.
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Titles By Michael Chappell
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.
This text is one of a number of appendices to the Oxford Neuroimaging Primers, designed to provide extra details and information that someone reading one of the primers might find helpful, but where it is not crucial to the understanding of the main material. This appendix specifically addresses the General Linear Model (GLM), as it is used in neuroimaging. In it we seek to go into more detail than we might in one of the primers, such as the Introduction to Neuroimaging Analysis, for those who want to understand more about how the GLM works and how to use it.
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.
This text is one of a number of appendices to the Oxford Neuroimaging Primers, designed to provide extra details and information that someone reading one of the primers might find helpful, but where it is not crucial to the understanding of the main material. This appendix specifically addresses the physical principles that underpin MRI, as it is used in neuroimaging. In it we seek to go into more detail than we might in one of the primers, such as the Introduction to Neuroimaging Analysis, for those who want to understand more about what is actually going on when we acquire MRI images of the brain. In turn, this appendix also provides more context on some of the decisions that are made when designing the most suitable acquisition for any given MRI modality for a particular imaging application or study design.
This book provides an introduction to qualitative and quantitative aspects of human physiology. It looks at 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, including 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 signal and imaging technologies. Physiology for Engineers describes the basic structure and models of cellular systems, the structure and function of the cardiovascular system, 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 is of interest to final year biomedical engineering undergraduates and graduate students alike, as well as to practising engineers new to the fields of bioengineering or medical physics.
This text is one of a number of appendices to the Oxford Neuroimaging Primers, designed to provide extra details and information that someone reading one of the primers might find helpful, but where it is not crucial to the understanding of the main material. This appendix specifically addresses the principles that underpin Bayesian Inference, as it is used in neuroimaging. In it we seek to go into more detail than we might in one of the primers, for those who want to understand more about how Bayesian Inference can be used for data analysis. In turn, this appendix also provides a high level introduction to individuals who are interested in developing their own Bayesian Inference methods, or find they need to select between different methods in a specific application.
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.