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Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging

MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers

  • Conference proceedings
  • © 2017

Overview

Editors:
  1. Henning Müller

    1. HES-SO, Sierre, Switzerland

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  2. B. Michael Kelm

    1. Siemens AG, Munich, Germany

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  3. Tal Arbel

    1. McGill University, Montreal, Canada

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  4. Weidong Cai

    1. University of Sydney, Sydney, Australia

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  5. M. Jorge Cardoso

    1. University College London, London, United Kingdom

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  6. Georg Langs

    1. Medical University of Vienna, Vienna, Austria

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  7. Bjoern Menze

    1. Technische Universität München, Garching, Germany

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  8. Dimitris Metaxas

    1. Rutgers The State University of New Jersey, Piscataway, USA

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  9. Albert Montillo

    1. University of Texas Southwestern Medical Center, Dallas, USA

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  10. William M. Wells III

    1. Brigham and Women’s Hospital, Boston, USA

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  11. Shaoting Zhang

    1. University of North Carolina at Charlotte, Charlotte, USA

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  12. Albert C.S. Chung

    1. The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong

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  13. Mark Jenkinson

    1. University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom

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  14. Annemie Ribbens

    1. IcoMetrix, Leuven, Belgium

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10081)

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

Included in the following conference series:

Conference proceedings info: BAMBI 2016, MCV 2016.

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Table of contents (19 papers)

  1. Front Matter

    Pages I-XIII
    Download chapter PDF

  2. MCV Workshop: Brain Imaging

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases

      • Ender Konukoglu, Ben Glocker
      Pages 3-13

    3. BigBrain: Automated Cortical Parcellation and Comparison with Existing Brain Atlases

      • Marc Fournier, Lindsay B. Lewis, Alan C. Evans
      Pages 14-25

    4. LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images

      • Li Wang, Yaozong Gao, Gang Li, Feng Shi, Weili Lin, Dinggang Shen
      Pages 26-34

    5. Landmark-Based Alzheimer’s Disease Diagnosis Using Longitudinal Structural MR Images

      • Jun Zhang, Mingxia Liu, Le An, Yaozong Gao, Dinggang Shen
      Pages 35-45

  3. MCV Workshop: Lung Imaging

    1. Front Matter

      Pages 47-47
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    2. Inferring Disease Status by Non-parametric Probabilistic Embedding

      • Nematollah Kayhan Batmanghelich, Ardavan Saeedi, Raul San Jose Estepar, Michael Cho, William M. Wells III
      Pages 49-57

    3. A Lung Graph–Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT Images

      • Yashin Dicente Cid, Henning Müller, Alexandra Platon, Jean–Paul Janssens, Frédéric Lador, Pierre–Alexandre Poletti et al.
      Pages 58-68

    4. Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study

      • Jie Yang, Elsa D. Angelini, Benjamin M. Smith, John H. M. Austin, Eric A. Hoffman, David A. Bluemke et al.
      Pages 69-80

  4. MCV Workshop: Segmentation, Detection, and Classification

    1. Front Matter

      Pages 81-81
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    2. Automatic Segmentation of Abdominal MRI Using Selective Sampling and Random Walker

      • Janine Thoma, Firat Ozdemir, Orcun Goksel
      Pages 83-93

    3. Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation

      • Naji Khosravan, Haydar Celik, Baris Turkbey, Ruida Cheng, Evan McCreedy, Matthew McAuliffe et al.
      Pages 94-104

    4. Automatic Detection of Histological Artifacts in Mouse Brain Slice Images

      • Nitin Agarwal, Xiangmin Xu, M. Gopi
      Pages 105-115

    5. Lung Nodule Classification by Jointly Using Visual Descriptors and Deep Features

      • Yutong Xie, Jianpeng Zhang, Sidong Liu, Weidong Cai, Yong Xia
      Pages 116-125

    6. Representation Learning for Cross-Modality Classification

      • Gijs van Tulder, Marleen de Bruijne
      Pages 126-136

    7. Guideline-Based Machine Learning for Standard Plane Extraction in 3D Cardiac Ultrasound

      • Peifei Zhu, Zisheng Li
      Pages 137-147

  5. BAMBI Workshop

    1. Front Matter

      Pages 149-149
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    2. A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images

      • Akshay Pai, Stefan Sommer, Lars Lau Raket, Line Kühnel, Sune Darkner, Lauge Sørensen et al.
      Pages 151-159

    3. Bayesian Multiview Manifold Learning Applied to Hippocampus Shape and Clinical Score Data

      • Giorgos Sfikas, Christophoros Nikou
      Pages 160-171
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  1. Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging

Keywords

About this book

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in Athens, Greece, in October 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016.
The 13 papers presented in MCV workshop and the 6 papers presented in BAMBI workshop were carefully reviewed and selected from numerous submissions.
The goal of the MCV workshop is to explore the use of "big data” algorithms for harvesting, organizing and learning from large-scale medical imaging data sets and for general-purpose automatic understanding of medical images.
The BAMBI workshop aims to highlight the potential of using Bayesian or random field graphical models for advancing research in biomedical image analysis.

Editors and Affiliations

  • HES-SO, Sierre, Switzerland

    Henning Müller

  • Siemens AG, Munich, Germany

    B. Michael Kelm

  • McGill University, Montreal, Canada

    Tal Arbel

  • University of Sydney, Sydney, Australia

    Weidong Cai

  • University College London, London, United Kingdom

    M. Jorge Cardoso

  • Medical University of Vienna, Vienna, Austria

    Georg Langs

  • Technische Universität München, Garching, Germany

    Bjoern Menze

  • Rutgers The State University of New Jersey, Piscataway, USA

    Dimitris Metaxas

  • University of Texas Southwestern Medical Center, Dallas, USA

    Albert Montillo

  • Brigham and Women’s Hospital, Boston, USA

    William M. Wells III

  • University of North Carolina at Charlotte, Charlotte, USA

    Shaoting Zhang

  • The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong

    Albert C.S. Chung

  • University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom

    Mark Jenkinson

  • IcoMetrix, Leuven, Belgium

    Annemie Ribbens

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