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Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics

First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10–14, 2017, Proceedings

  • Conference proceedings
  • © 2017

Overview

Editors:
  1. M. Jorge Cardoso

    1. University College London, London, United Kingdom

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  2. Tal Arbel

    1. McGill University, Montreal, Canada

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  3. Enzo Ferrante

    1. Imperial College London, London, United Kingdom

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  4. Xavier Pennec

    1. Inria Sophia, Sophia-Antipolis, France

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  5. Adrian V. Dalca

    1. Harvard Medical School, Massachusetts Institute of Technology, Boston, USA

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  6. Sarah Parisot

    1. Imperial College London, London, United Kingdom

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  7. Sarang Joshi

    1. University of Utah, Salt Lake City, USA

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  8. Nematollah K. Batmanghelich

    1. University of Pennsylvania, Philadelphia, USA

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  9. Aristeidis Sotiras

    1. University of Pennsylvania, Philadelphia, USA

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  10. Mads Nielsen

    1. University of Copenhagen, Copenhagen, Denmark

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  11. Mert R. Sabuncu

    1. Cornell University, Ithaca, USA

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  12. Tom Fletcher

    1. University of Utah, Salt Lake City, USA

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  13. Li Shen

    1. University of Indiana, Indianapolis, USA

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  14. Stanley Durrleman

    1. Brain and Spine Institute, Inria, Paris, France

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  15. Stefan Sommer

    1. University of Copenhagen, Copenhagen, Denmark

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10551)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

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Table of contents (22 papers)

  1. Front Matter

    Pages I-XV
    Download chapter PDF

  2. First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017

    1. Front Matter

      Pages 1-1
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    2. Classifying Phenotypes Based on the Community Structure of Human Brain Networks

      • Anvar Kurmukov, Marina Ananyeva, Yulia Dodonova, Boris Gutman, Joshua Faskowitz, Neda Jahanshad et al.
      Pages 3-11

    3. Autism Spectrum Disorder Diagnosis Using Sparse Graph Embedding of Morphological Brain Networks

      • Carrie Morris, Islem Rekik
      Pages 12-20

    4. Topology of Surface Displacement Shape Feature in Subcortical Structures

      • Amanmeet Garg, Donghuan Lu, Karteek Popuri, Mirza Faisal Beg
      Pages 21-30

    5. Graph Geodesics to Find Progressively Similar Skin Lesion Images

      • Jeremy Kawahara, Kathleen P. Moriarty, Ghassan Hamarneh
      Pages 31-41

    6. Uncertainty Estimation in Vascular Networks

      • Markus Rempfler, Bjoern Andres, Bjoern H. Menze
      Pages 42-52

    7. Extraction of Airways with Probabilistic State-Space Models and Bayesian Smoothing

      • Raghavendra Selvan, Jens Petersen, Jesper H. Pedersen, Marleen de Bruijne
      Pages 53-63

    8. Detection and Localization of Landmarks in the Lower Extremities Using an Automatically Learned Conditional Random Field

      • Alexander Oliver Mader, Cristian Lorenz, Martin Bergtholdt, Jens  von  Berg, Hauke Schramm, Jan Modersitzki et al.
      Pages 64-75

  3. 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017

    1. Front Matter

      Pages 77-77
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    2. Bridge Simulation and Metric Estimation on Landmark Manifolds

      • Stefan Sommer, Alexis Arnaudon, Line Kuhnel, Sarang Joshi
      Pages 79-91

    3. White Matter Fiber Segmentation Using Functional Varifolds

      • Kuldeep Kumar, Pietro Gori, Benjamin Charlier, Stanley Durrleman, Olivier Colliot, Christian Desrosiers
      Pages 92-100

    4. Prediction of the Progression of Subcortical Brain Structures in Alzheimer’s Disease from Baseline

      • Alexandre Bône, Maxime Louis, Alexandre Routier, Jorge Samper, Michael Bacci, Benjamin Charlier et al.
      Pages 101-113

    5. A New Metric for Statistical Analysis of Rigid Transformations: Application to the Rib Cage

      • Baptiste Moreau, Benjamin Gilles, Erwan Jolivet, Philippe Petit, Gérard Subsol
      Pages 114-124

    6. Unbiased Diffeomorphic Mapping of Longitudinal Data with Simultaneous Subject Specific Template Estimation

      • Daniel Tward, Michael Miller, the Alzheimer’s Disease Neuroimaging Initiative
      Pages 125-136

    7. Exact Function Alignment Under Elastic Riemannian Metric

      • Daniel Robinson, Adam Duncan, Anuj Srivastava, Eric Klassen
      Pages 137-151

    8. Varifold-Based Matching of Curves via Sobolev-Type Riemannian Metrics

      • Martin Bauer, Martins Bruveris, Nicolas Charon, Jakob Møller-Andersen
      Pages 152-163

    9. Computational Anatomy in Theano

      • Line Kühnel, Stefan Sommer
      Pages 164-176

    10. Rank Constrained Diffeomorphic Density Motion Estimation for Respiratory Correlated Computed Tomography

      • Markus Foote, Pouya Sabouri, Amit Sawant, Sarang Joshi
      Pages 177-185

    11. Efficient Parallel Transport in the Group of Diffeomorphisms via Reduction to the Lie Algebra

      • Kristen M. Campbell, P. Thomas Fletcher
      Pages 186-198
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  1. Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics

Keywords

About this book

This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017.

The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.


Editors and Affiliations

  • University College London, London, United Kingdom

    M. Jorge Cardoso

  • McGill University, Montreal, Canada

    Tal Arbel

  • Imperial College London, London, United Kingdom

    Enzo Ferrante, Sarah Parisot

  • Inria Sophia, Sophia-Antipolis, France

    Xavier Pennec

  • Harvard Medical School, Massachusetts Institute of Technology, Boston, USA

    Adrian V. Dalca

  • University of Utah, Salt Lake City, USA

    Sarang Joshi, Tom Fletcher

  • University of Pennsylvania, Philadelphia, USA

    Nematollah K. Batmanghelich, Aristeidis Sotiras

  • University of Copenhagen, Copenhagen, Denmark

    Mads Nielsen, Stefan Sommer

  • Cornell University, Ithaca, USA

    Mert R. Sabuncu

  • University of Indiana, Indianapolis, USA

    Li Shen

  • Brain and Spine Institute, Inria, Paris, France

    Stanley Durrleman

Bibliographic Information

  • Book Title: Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics

  • Book Subtitle: First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10–14, 2017, Proceedings

  • Editors: M. Jorge Cardoso, Tal Arbel, Enzo Ferrante, Xavier Pennec, Adrian V. Dalca, Sarah Parisot, Sarang Joshi, Nematollah K. Batmanghelich, Aristeidis Sotiras, Mads Nielsen, Mert R. Sabuncu, Tom Fletcher, Li Shen, Stanley Durrleman, … Stefan Sommer

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-319-67675-3

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing AG 2017

  • Softcover ISBN: 978-3-319-67674-6Published: 09 September 2017

  • eBook ISBN: 978-3-319-67675-3Published: 06 September 2017

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XV, 250

  • Number of Illustrations: 83 b/w illustrations

  • Topics: Image Processing and Computer Vision, Pattern Recognition, Artificial Intelligence, Health Informatics, Data Mining and Knowledge Discovery

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