Understanding and Interpreting Machine Learning in Medical Image Computing Applications

First International Workshops, MLCN 2018, DLF 2018, and iMIMIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018, Proceedings

  • Danail Stoyanov
  • Zeike Taylor
  • Seyed Mostafa Kia
  • Ipek Oguz
  • Mauricio Reyes
  • Anne Martel
  • Lena Maier-Hein
  • Andre F. Marquand
  • Edouard Duchesnay
  • Tommy Löfstedt
  • Bennett Landman
  • M. Jorge Cardoso
  • Carlos A. Silva
  • Sergio Pereira
  • Raphael Meier
Conference proceedings MLCN 2018, DLF 2018, IMIMIC 2018

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11038)

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 11038)

Table of contents

  1. Front Matter
    Pages I-XVI
  2. First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018

    1. Front Matter
      Pages 1-1
    2. Clement Abi Nader, Nicholas Ayache, Philippe Robert, Marco Lorenzi, for the Alzheimer’s Disease Neuroimaging Initiative
      Pages 3-14
    3. Luigi Antelmi, Nicholas Ayache, Philippe Robert, Marco Lorenzi, for the Alzheimer’s Disease Neuroimaging Initiative
      Pages 15-23
    4. Johannes Rieke, Fabian Eitel, Martin Weygandt, John-Dylan Haynes, Kerstin Ritter
      Pages 24-31
  3. First International Workshop on Deep Learning Fails Workshop, DLF 2018

    1. Front Matter
      Pages 41-41
    2. Yuanyuan Sun, Adriaan Moelker, Wiro J. Niessen, Theo van Walsum
      Pages 43-51
    3. Aabhas Majumdar, Raghav Mehta, Jayanthi Sivaswamy
      Pages 52-60
    4. James R. Clough, Daniel R. Balfour, Claudia Prieto, Andrew J. Reader, Paul K. Marsden, Andrew P. King
      Pages 61-69
    5. David Kügler, Alexander Distergoft, Arjan Kuijper, Anirban Mukhopadhyay
      Pages 70-78
    6. Muhan Shao, Shuo Han, Aaron Carass, Xiang Li, Ari M. Blitz, Jerry L. Prince et al.
      Pages 79-86
    7. Saeid Asgari Taghanaki, Arkadeep Das, Ghassan Hamarneh
      Pages 87-94
  4. First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018

    1. Front Matter
      Pages 95-95
    2. Noel C. F. Codella, Chung-Ching Lin, Allan Halpern, Michael Hind, Rogerio Feris, John R. Smith
      Pages 97-105
    3. Sérgio Pereira, Raphael Meier, Victor Alves, Mauricio Reyes, Carlos A. Silva
      Pages 106-114
    4. Pieter Van Molle, Miguel De Strooper, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt
      Pages 115-123
    5. Mara Graziani, Vincent Andrearczyk, Henning Müller
      Pages 124-132
    6. Wilson Silva, Kelwin Fernandes, Maria J. Cardoso, Jaime S. Cardoso
      Pages 133-140
    7. Mahya Sadeghi, Parmit K. Chilana, M. Stella Atkins
      Pages 141-148
  5. Back Matter
    Pages 149-149

About these proceedings


This book constitutes the refereed joint proceedings of the First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018, the First International Workshop on Deep Learning Fails, DLF 2018, and the First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018.

The 4 full MLCN papers, the 6 full DLF papers, and the 6 full iMIMIC papers included in this volume were carefully reviewed and selected. The MLCN contributions develop state-of-the-art machine learning methods such as spatio-temporal Gaussian process analysis, stochastic variational inference, and deep learning for applications in Alzheimer's disease diagnosis and multi-site neuroimaging data analysis; the DLF papers evaluate the strengths and weaknesses of DL and identify the main challenges in the current state of the art and future directions; the iMIMIC papers cover a large range of topics in the field of interpretability of machine learning in the context of medical image analysis.  


artificial intelligence biocommunications bioinformatics biomedical technologies classification computer vision decision support systems deep learning fuzzy logic fuzzy models fuzzy systems image analysis image reconstruction image segmentation machine learning medical image computing medical images motion estimation neural networks semantics

Editors and affiliations

  1. 1.University College LondonLondonUK
  2. 2.University of LeedsLeedsUK
  3. 3.Radboud University Medical CenterNijmegenThe Netherlands
  4. 4.Vanderbilt UniversityNashvilleUSA
  5. 5.University of BernBernSwitzerland
  6. 6.Sunnybrook Research InstituteTorontoCanada
  7. 7.German Cancer Research Center (DKFZ)HeidelbergGermany
  8. 8.Radboud University Nijmegen Medical CenterNijmegenThe Netherlands
  9. 9.NeuroSpin, CEA SaclayGif-sur-YvetteFrance
  10. 10.Umeå UniversityUmeåSweden
  11. 11.Vanderbilt UniversityNashvilleUSA
  12. 12.King's College LondonLondonUK
  13. 13.University of MinhoGuimarãesPortugal
  14. 14.University of MinhoGuimarãesPortugal
  15. 15.University Hospital InselspitalBernSwitzerland

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