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Spectral and Shape Analysis in Medical Imaging: First International Workshop, SeSAMI 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Revised Selected Papers

✍ Scribed by Martin Reuter, Christian Wachinger, Hervé Lombaert (eds.)


Publisher
Springer International Publishing
Year
2016
Tongue
English
Leaves
138
Series
Lecture Notes in Computer Science 10126
Edition
1
Category
Library

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✦ Synopsis


This book constitutes the refereed post-conference proceedings of the First International Workshop on Spectral and Shape Analysis in Medical Imaging, SeSAMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016.
The 10 submitted full papers presented in this volume were carefully reviewed.
The papers reflect the following topics: spectral methods; longitudinal methods; and shape methods.

✦ Table of Contents


Front Matter....Pages I-VIII
Front Matter....Pages 1-1
A Volumetric Conformal Mapping Approach for Clustering White Matter Fibers in the Brain....Pages 3-14
Deep Spectral-Based Shape Features for Alzheimer’s Disease Classification....Pages 15-24
Functional Maps for Brain Classification on Spectral Domain....Pages 25-36
Front Matter....Pages 37-37
Volume Representation of Parenchymatous Organs by Volumetric Self-organizing Deformable Model....Pages 39-50
Reducing Variability in Anatomical Definitions Over Time Using Longitudinal Diffeomorphic Mapping....Pages 51-62
Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease....Pages 63-75
Front Matter....Pages 77-77
Longitudinal Scoliotic Trunk Analysis via Spectral Representation and Statistical Analysis....Pages 79-91
Statistical Shape Model with Random Walks for Inner Ear Segmentation....Pages 92-102
Volumetric Image Pattern Recognition Using Three-Way Principal Component Analysis....Pages 103-117
Shape Preservation Based on Gaussian Radial Basis Function Interpolation on Human Corpus Callosum....Pages 118-132
Back Matter....Pages 133-133

✦ Subjects


Image Processing and Computer Vision;Health Informatics;Artificial Intelligence (incl. Robotics);Pattern Recognition;Data Mining and Knowledge Discovery


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