Abstract
After defining the medical image registration problem, we provide a short introduction to a select group of multi-modal image alignment approaches. More precisely, we choose four widely-used statistical methods applied in registration scenarios for analysis and comparison. We clarify the implicit and explicit assumptions made by each, aiming to yield a better understanding of their relative strengths and weaknesses. We also introduce a figural representation of the methods in order to provide an intuitive way of illustrating their similarities and differences.
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© 2006 Springer Science+Business Media, Inc.
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Zöliei, L., Fisher, J., Wells, W. (2006). An Introduction to Statistical Methods of Medical Image Registration. In: Paragios, N., Chen, Y., Faugeras, O. (eds) Handbook of Mathematical Models in Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/0-387-28831-7_33
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DOI: https://doi.org/10.1007/0-387-28831-7_33
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-26371-7
Online ISBN: 978-0-387-28831-4
eBook Packages: Computer ScienceComputer Science (R0)