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Numerical Methods for Image Registration (Numerical Mathematics and Scientific Computation)
 
 

Numerical Methods for Image Registration (Numerical Mathematics and Scientific Computation) [Hardcover]

Jan Modersitzki (Author)

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Book Description

0198528418 978-0198528418 February 12, 2004 1
Based on the author's lecture notes and research, this well-illustrated and comprehensive text is one of the first to provide an introduction to image registration with particular emphasis on numerical methods in medical imaging. Ideal for researchers in industry and academia, it is also a suitable study guide for graduate mathematicians, computer scientists, engineers, medical physicists and radiologists. Image registration is utilized whenever information obtained from different viewpoints needs to be combined or compared and unwanted distortion needs to be eliminated. For example, CCTV images, ultrasound images, brain scan images, fingerprint and retinal scanning. Modersitzki's book provides a systematic introduction to the theoretical, practical, and numerical aspects of image registration, with special emphasis on medical applications. Various techniques are described, discussed and compared using numerous illustrations. The text starts with an introduction to the mathematical principles and the motivating example of the Human Neuroscanning Project whose aim is to build an atlas of the human brain through reconstructing essential information out of deformed images of sections of a prepared brain. The introduction is followed by coverage of parametric image registrations such as landmark based, principal axes based and optimal affine linear registration. Basic distance measures like sum of squared differences, correlation and mutual information are also discussed. The next section is devoted to state-of-the-art non-parametric image registrations where general variation based framework for image registration is presented and used to describe and compare well-known and new image registration techniques. Finally, efficient numerical schemes for the underlying partial differential equations are presented and discussed. This text treats the basic mathematical principles, including aspects from approximation theory, image processing, numrics, partial differential equations, and statistics, with a strong focus on numerical methods in image processing. Providing a systematic and general framework for image registration, the book not only presents state-of-the-art concepts but also summarizes and classifies the numerous techniques to be found in the literature.

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Editorial Reviews

Review

`In Numerical Methods for Image Registration, author Jan Modersitzki presents a well-focused text on the solutions to a particular problem in the field of computer vision and image processing--image registration. I certainly recommend the book for researchers as well as mathematically inclined practitioners in the field of image processing and computer vision. ' Gurusham Sudhir in The Industrial Physicist

`This book is definitely award-worthy in its timeliness, clarity, completeness, and impotrance. This reviewer personally votes for this work as the best in 2004 in the area of imaging sciences.' Jianhong Shen in Mathematical Reviews 2005h

About the Author

Jan Modersitzki is at Institute of Mathematics, University of Lubeck.

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Inside This Book (learn more)
First Sentence:
In image processing one is often interested not only in analyzing one image but in comparing or combining the information given by different images. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
curvature registration, diffusion registration, fluid registration, matrix stencils, elastic registration, sliding boundary conditions, linear registration, deformed template, medical image registration, template image, registration results, worthwhile noticing, registration techniques, solution scheme, registration schemes, mutual information, elastic potential, norm solution
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Proof Follows, Math Works
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