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Machine Learning Meets Medical Imaging

First International Workshop, MLMMI 2015, Held in Conjunction with ICML 2015, Lille, France, July 11, 2015, Revised Selected Papers

  • Conference proceedings
  • © 2015

Overview

Editors:
  1. Kanwal Bhatia

    1. Imperial College , London, United Kingdom

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    You can also search for this editor in PubMed   Google Scholar

  2. Herve Lombaert

    1. INRIA Sophia-Antipolis , Valbonne, France

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9487)

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

Included in the following conference series:

Conference proceedings info: MLMMI 2015.

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Table of contents (10 papers)

  1. Front Matter

    Pages I-X
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  2. Motion

    1. Front Matter

      Pages 1-1
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    2. Retrospective Motion Correction of Magnitude-Input MR Images

      • Alexander Loktyushin, Christian Schuler, Klaus Scheffler, Bernhard Schölkopf
      Pages 3-12

    3. Automatic Brain Localization in Fetal MRI Using Superpixel Graphs

      • Amir Alansary, Matthew Lee, Kevin Keraudren, Bernhard Kainz, Christina Malamateniou, Mary Rutherford et al.
      Pages 13-22

  3. Brain

    1. Front Matter

      Pages 23-23
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    2. Learning Deep Temporal Representations for fMRI Brain Decoding

      • Orhan Firat, Emre Aksan, Ilke Oztekin, Fatos T. Yarman Vural
      Pages 25-34

    3. Modelling Non-stationary and Non-separable Spatio-Temporal Changes in Neurodegeneration via Gaussian Process Convolution

      • Lorenzi Marco, Gabriel Ziegler, Daniel C. Alexander, Sebastien Ourselin
      Pages 35-44

    4. Improving MRI Brain Image Classification with Anatomical Regional Kernels

      • Jonathan Young, Alex Mendelson, M. Jorge Cardoso, Marc Modat, John Ashburner, Sebastien Ourselin
      Pages 45-53

  4. Computer Aided Diagnosis

    1. Front Matter

      Pages 55-55
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    2. A Graph Based Classification Method for Multiple Sclerosis Clinical Forms Using Support Vector Machine

      • Claudio Stamile, Gabriel Kocevar, Salem Hannoun, Françoise Durand-Dubief, Dominique Sappey-Marinier
      Pages 57-64

    3. Classification of Alzheimer’s Disease Using Discriminant Manifolds of Hippocampus Shapes

      • Mahsa Shakeri, Hervé Lombaert, Samuel Kadoury
      Pages 65-73

    4. Transfer Learning for Prostate Cancer Mapping Based on Multicentric MR Imaging Databases

      • Rahaf Aljundi, Jérôme Lehaire, Fabrice Prost-Boucle, Olivier Rouvière, Carole Lartizien
      Pages 74-82

  5. Segmentation

    1. Front Matter

      Pages 83-83
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    2. Feature-Space Transformation Improves Supervised Segmentation Across Scanners

      • Annegreet van Opbroek, Hakim C. Achterberg, Marleen de Bruijne
      Pages 85-93

    3. Discriminative Dimensionality Reduction for Patch-Based Label Fusion

      • Gerard Sanroma, Oualid M. Benkarim, Gemma Piella, Guorong Wu, Xiaofeng Zhu, Dinggang Shen et al.
      Pages 94-103

  6. Back Matter

    Pages 105-105
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About this book

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The 10 papers presented in this volume were carefully reviewed and selected for inclusion in the book. The papers communicate the specific needs and nuances of medical imaging to the machine learning community while exposing the medical imaging community to current trends in machine learning.

 

Editors and Affiliations

  • Imperial College , London, United Kingdom

    Kanwal Bhatia

  • INRIA Sophia-Antipolis , Valbonne, France

    Herve Lombaert

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