Handbook of Neuroimaging Data Analysis
Abstract
This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.
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One widely used hypothesis-driven analysis assesses statistical differences of tracts of interest between groups using statistical group-wise comparison methods such as Student's t-test, ANOVA, or more advanced methods.
“Usually, given a quantitative measure of interest, a selected summary statistic (e.g. mean of the chosen microstructural measure) is extracted from the tract(s)-of-interest and is used to compute the level of group differences (e.g., the p-value) using statistical group-wise comparison methods such as Student’s t-test, ANOVA, or other more advanced statistical analysis methods (Habeck and Stern, 2”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Ombao et al., 2016
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“ANOVA, or other more advanced statistical analysis methods (Habeck and Stern, 2010; Martí-Juan et al., 2020; Ombao et al., 2016; Zhang et al., 2018b).”
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- Authors
- Ombao, H., Lindquist, M., Thompson, W., & Aston, J. A. D.
- Affiliations
- Johns Hopkins University (US)
- ORCID
- John A. D. Aston
- Venue
- Chapman & Hall/CRC eBooks
- Publisher
- Chapman and Hall/CRC
- Published
- 2016-11-18
- OpenAlex
- W2897579508
- Cited by
- 80
- References
- 0
- Citations by year
- 2025: 9 · 2024: 13 · 2023: 16 · 2022: 7 · 2021: 10 · 2020: 10 · 2019: 6 · 2018: 6 · 2017: 2 · 2016: 1
- FWCI
- 2.63
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Chapman & Hall/CRC eBooks (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- neuroimaging data analysis, neuroimaging
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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