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Cover image for Statistical and computational methods in brain image analysis
Title:
Statistical and computational methods in brain image analysis
Author:
Chung, Moo K., author.
ISBN:
9780429094323
Physical Description:
1 online resource (xvi, 400 pages)
Series:
Chapman & Hall/CRC mathematical and computational imaging sciences

Chapman & Hall/CRC mathematical and computational imaging sciences.
Contents:
1. Introduction to brain and medical images -- 2. Bernoulli models for binary images -- 3. General linear models -- 4. Gaussian kernel smoothing -- 5. Random fields theory -- 6. Anisotropic kernel smoothing -- 7. Multivariate general linear models -- 8. Cortical surface analysis -- 9. Heat kernel smoothing on surfaces -- 10. Cosine series representation of 3D curves -- 11. Weighted spherical harmonic representation -- 12. Multivariate surface shape analysis -- 13. Laplace-Beltrami Eigenfunctions for surface data -- 14. Persistent homology -- 15. Sparse networks -- 16. Sparse shape models -- 17. Modeling structural brain networks -- 18. Mixed effects models.
Abstract:
The massive amount of nonstandard high-dimensional brain imaging data being generated is often difficult to analyze using current techniques. This challenge in brain image analysis requires new computational approaches and solutions. But none of the research papers or books in the field describe the quantitative techniques with detailed illustrations of actual imaging data and computer codes. Using MATLAB and case study data sets, Statistical and Computational Methods in Brain Image Analysis is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book focuses on methodological issues in analyzing structural brain imaging modalities such as MRI and DTI. Real imaging applications and examples elucidate the concepts and methods. In addition, most of the brain imaging data sets and MATLAB codes are available on the author's website. By supplying the data and codes, this book enables researchers to start their statistical analyses immediately. Also suitable for graduate students, it provides an understanding of the various statistical and computational methodologies used in the field as well as important and technically challenging topics.-- Provided by publisher.
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E-Book 541705-1001 RC386.6 .D52 C48 2014
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