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Spectral and Shape Analysis in Medical Imaging

Overview of attention for book
Cover of 'Spectral and Shape Analysis in Medical Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 A Volumetric Conformal Mapping Approach for Clustering White Matter Fibers in the Brain
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    Chapter 2 Deep Spectral-Based Shape Features for Alzheimer’s Disease Classification
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    Chapter 3 Functional Maps for Brain Classification on Spectral Domain
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    Chapter 4 Volume Representation of Parenchymatous Organs by Volumetric Self-organizing Deformable Model
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    Chapter 5 Reducing Variability in Anatomical Definitions Over Time Using Longitudinal Diffeomorphic Mapping
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    Chapter 6 Spectral and Shape Analysis in Medical Imaging
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    Chapter 7 Longitudinal Scoliotic Trunk Analysis via Spectral Representation and Statistical Analysis
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    Chapter 8 Statistical Shape Model with Random Walks for Inner Ear Segmentation
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    Chapter 9 Volumetric Image Pattern Recognition Using Three-Way Principal Component Analysis
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    Chapter 10 Shape Preservation Based on Gaussian Radial Basis Function Interpolation on Human Corpus Callosum
Attention for Chapter 4: Volume Representation of Parenchymatous Organs by Volumetric Self-organizing Deformable Model
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Citations

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Chapter title
Volume Representation of Parenchymatous Organs by Volumetric Self-organizing Deformable Model
Chapter number 4
Book title
Spectral and Shape Analysis in Medical Imaging
Published by
Springer, Cham, October 2016
DOI 10.1007/978-3-319-51237-2_4
Book ISBNs
978-3-31-951236-5, 978-3-31-951237-2
Authors

Shoko Miyauchi, Ken’ichi Morooka, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 50%
Unknown 2 50%
Readers by discipline Count As %
Computer Science 1 25%
Neuroscience 1 25%
Unknown 2 50%

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