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Computational Diffusion MRI

Overview of attention for book
Cover of 'Computational Diffusion MRI'

Table of Contents

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    Book Overview
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    Chapter 1 Slice Estimation in Diffusion MRI of Neonatal and Fetal Brains in Image and Spherical Harmonics Domains Using Autoencoders
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    Chapter 2 Super-Resolution of Manifold-Valued Diffusion MRI Refined by Multi-modal Imaging
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    Chapter 3 Lossy Compression of Multidimensional Medical Images Using Sinusoidal Activation Networks: An Evaluation Study
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    Chapter 4 Correction of Susceptibility Distortion in EPI: A Semi-supervised Approach with Deep Learning
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    Chapter 5 The Impact of Susceptibility Distortion Correction Protocols on Adolescent Diffusion MRI Measures
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    Chapter 6 Diffusion MRI Fibre Orientation Distribution Inpainting
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    Chapter 7 Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-supervised Machine Learning
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    Chapter 8 Stepwise Stochastic Dictionary Adaptation Improves Microstructure Reconstruction with Orientation Distribution Function Fingerprinting
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    Chapter 9 How Can Spherical CNNs Benefit ML-Based Diffusion MRI Parameter Estimation?
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    Chapter 10 DC $$^2$$ 2 U-Net: Tract Segmentation in Brain White Matter Using Dense Criss-Cross U-Net
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    Chapter 11 Clustering in Tractography Using Autoencoders (CINTA)
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    Chapter 12 Tractometric Coherence of Fiber Bundles in DTI
Attention for Chapter 9: How Can Spherical CNNs Benefit ML-Based Diffusion MRI Parameter Estimation?
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Chapter title
How Can Spherical CNNs Benefit ML-Based Diffusion MRI Parameter Estimation?
Chapter number 9
Book title
Computational Diffusion MRI
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-21206-2_9
Book ISBNs
978-3-03-121205-5, 978-3-03-121206-2
Authors

Goodwin-Allcock, Tobias, McEwen, Jason, Gray, Robert, Nachev, Parashkev, Zhang, Hui, Goodwin-Allcock, T, McEwen, J, Gray, R, Nachev, P, Zhang, H

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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 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 17%
Lecturer 1 17%
Student > Master 1 17%
Unknown 3 50%
Readers by discipline Count As %
Mathematics 2 33%
Computer Science 1 17%
Unknown 3 50%

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