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Bayesian and grAphical Models for Biomedical Imaging

Overview of attention for book
Cover of 'Bayesian and grAphical Models for Biomedical Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 N3 Bias Field Correction Explained as a Bayesian Modeling Method
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    Chapter 2 A Bayesian Approach to Distinguishing Interdigitated Muscles in the Tongue from Limited Diffusion Weighted Imaging
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    Chapter 3 Optimal Joint Segmentation and Tracking of Escherichia Coli in the Mother Machine
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    Chapter 4 Physiologically Informed Bayesian Analysis of ASL fMRI Data
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    Chapter 5 Bone Reposition Planning for Corrective Surgery Using Statistical Shape Model: Assessment of Differential Geometrical Features
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    Chapter 6 An Inference Language for Imaging
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    Chapter 7 An MRF-Based Discrete Optimization Framework for Combined DCE-MRI Motion Correction and Pharmacokinetic Parameter Estimation
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    Chapter 8 Learning Imaging Biomarker Trajectories from Noisy Alzheimer’s Disease Data Using a Bayesian Multilevel Model
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    Chapter 9 Four Neuroimaging Questions that P-Values Cannot Answer (and Bayesian Analysis Can)
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    Chapter 10 Spherical Topic Models for Imaging Phenotype Discovery in Genetic Studies.
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    Chapter 11 A Generative Model for Automatic Detection of Resolving Multiple Sclerosis Lesions
Attention for Chapter 9: Four Neuroimaging Questions that P-Values Cannot Answer (and Bayesian Analysis Can)
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Chapter title
Four Neuroimaging Questions that P-Values Cannot Answer (and Bayesian Analysis Can)
Chapter number 9
Book title
Bayesian and grAphical Models for Biomedical Imaging
Published by
Springer, Cham, January 2014
DOI 10.1007/978-3-319-12289-2_9
Book ISBNs
978-3-31-912288-5, 978-3-31-912289-2
Authors

Maxime Taquet, Jurriaan M. Peters, Simon K. Warfield, Taquet, Maxime, Peters, Jurriaan M., Warfield, Simon K.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 11%
France 1 11%
Unknown 7 78%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 33%
Other 1 11%
Professor 1 11%
Student > Doctoral Student 1 11%
Student > Ph. D. Student 1 11%
Other 1 11%
Unknown 1 11%
Readers by discipline Count As %
Neuroscience 2 22%
Computer Science 1 11%
Psychology 1 11%
Medicine and Dentistry 1 11%
Unknown 4 44%

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