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.
Michael Chappell & Mark Jenkinson
Introduction to Neuroimaging Analysis [EPUB ebook]
Introduction to Neuroimaging Analysis [EPUB ebook]
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Limba Engleză ● Format EPUB ● Pagini 208 ● ISBN 9780192548276 ● Editura OUP Oxford ● Publicat 2018 ● Descărcabil 3 ori ● Valută EUR ● ID 8103168 ● Protecție împotriva copiilor Adobe DRM
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