Michael Chappell

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.

From Signals to Images

Principles of Medical Imaging for Engineers

Mark Jenkinson

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 anunderstanding 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 approachableintroduction 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 andinterpretation. 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.

Michael Chappell

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