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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

  • Martin Reuter
  • Christian Wachinger
  • Hervé Lombaert
Conference proceedings SeSAMI 2016

Part of the Lecture Notes in Computer Science book series (LNCS, volume 10126)

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 10126)

Table of contents

  1. Front Matter
    Pages I-VIII
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  2. Spectral Methods

    1. Front Matter
      Pages 1-1
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    2. A Volumetric Conformal Mapping Approach for Clustering White Matter Fibers in the Brain
      Vikash Gupta, Gautam Prasad, Paul Thompson
      Pages 3-14
    3. Deep Spectral-Based Shape Features for Alzheimer’s Disease Classification
      Mahsa Shakeri, Herve Lombaert, Shashank Tripathi, Samuel Kadoury, for the Alzheimer’s Disease Neuroimaging Initiative
      Pages 15-24
    4. Functional Maps for Brain Classification on Spectral Domain
      Simone Melzi, Alessandro Mella, Letizia Squarcina, Marcella Bellani, Cinzia Perlini, Mirella Ruggeri et al.
      Pages 25-36

  3. Longitudinal Methods

    1. Front Matter
      Pages 37-37
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    2. Volume Representation of Parenchymatous Organs by Volumetric Self-organizing Deformable Model
      Shoko Miyauchi, Ken’ichi Morooka, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume
      Pages 39-50
    3. Reducing Variability in Anatomical Definitions Over Time Using Longitudinal Diffeomorphic Mapping
      Daniel J. Tward, Chelsea S. Sicat, Timothy Brown, Arnold Bakker, Michael I. Miller
      Pages 51-62
    4. Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease
      Claire Cury, Marco Lorenzi, David Cash, Jennifer M. Nicholas, Alexandre Routier, Jonathan Rohrer et al.
      Pages 63-75

  4. Shape Methods

    1. Front Matter
      Pages 77-77
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    2. Longitudinal Scoliotic Trunk Analysis via Spectral Representation and Statistical Analysis
      Ola Ahmad, Herve Lombaert, Stefan Parent, Hubert Labelle, Jean Dansereau, Farida Cheriet
      Pages 79-91
    3. Statistical Shape Model with Random Walks for Inner Ear Segmentation
      Esmeralda Ruiz Pujadas, Hans Martin Kjer, Gemma Piella, Miguel Angel González Ballester
      Pages 92-102
    4. Volumetric Image Pattern Recognition Using Three-Way Principal Component Analysis
      Hayato Itoh, Atsushi Imiya, Tomoya Sakai
      Pages 103-117
    5. Shape Preservation Based on Gaussian Radial Basis Function Interpolation on Human Corpus Callosum
      Umut Orcun Turgut, Didem Gokcay
      Pages 118-132
  5. Back Matter
    Pages 133-133
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About these proceedings

Introduction

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.

Keywords

anatomical modeling computer-aided diagnosis geometry processing medical image computing structural MRI brain classification cochlea segmentation dimensionality reduction functional analysis longitudinal shape analysis medical applications mesh segmentation ; registration segmentation shape analysis shape modeling spectral analysis statistical shape analysis volumetric parameterization

Editors and affiliations

  • Martin Reuter
    • 1
  • Christian Wachinger
    • 2
  • Hervé Lombaert
    • 3
  1. 1.Harvard Medical SchoolBostonUSA
  2. 2.Ludwig-Maximilian University of MunichMunichGermany
  3. 3.Inria Sophia AntipolisSophia AntipolisFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-51237-2
  • Copyright Information Springer International Publishing AG 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-51236-5
  • Online ISBN 978-3-319-51237-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site