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ORCIDMLCN/DLF/iMIMIC@MICCAI 2018: Granada, Spain
- Danail Stoyanov, Zeike Taylor, Seyed Mostafa Kia, Ipek Oguz, Mauricio Reyes, Anne L. Martel, Lena Maier-Hein, Andre F. Marquand, Edouard Duchesnay, Tommy Löfstedt, Bennett A. Landman, M. Jorge Cardoso, Carlos A. Silva, Sérgio Pereira, Raphael Meier:
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. Lecture Notes in Computer Science 11038, Springer 2018, ISBN 978-3-030-02627-1
First International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2018
- Clément Abi Nader, Nicholas Ayache, Philippe Robert, Marco Lorenzi:
Alzheimer's Disease Modelling and Staging Through Independent Gaussian Process Analysis of Spatio-Temporal Brain Changes. 3-14 - Luigi Antelmi
, Nicholas Ayache, Philippe Robert, Marco Lorenzi:
Multi-channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease. 15-23 - Johannes Rieke, Fabian Eitel, Martin Weygandt, John-Dylan Haynes, Kerstin Ritter:
Visualizing Convolutional Networks for MRI-Based Diagnosis of Alzheimer's Disease. 24-31 - Roberto Vega, Russell Greiner:
Finding Effective Ways to (Machine) Learn fMRI-Based Classifiers from Multi-site Data. 32-39
First International Workshop on Deep Learning Fails Workshop, DLF 2018
- Yuanyuan Sun, Adriaan Moelker, Wiro J. Niessen, Theo van Walsum:
Towards Robust CT-Ultrasound Registration Using Deep Learning Methods. 43-51 - Aabhas Majumdar, Raghav Mehta, Jayanthi Sivaswamy:
To Learn or Not to Learn Features for Deformable Registration? 52-60 - James R. Clough, Daniel R. Balfour, Claudia Prieto, Andrew J. Reader, Paul K. Marsden, Andrew P. King:
Evaluation of Strategies for PET Motion Correction - Manifold Learning vs. Deep Learning. 61-69 - David Kügler, Alexander Distergoft, Arjan Kuijper, Anirban Mukhopadhyay:
Exploring Adversarial Examples - Patterns of One-Pixel Attacks. 70-78 - Muhan Shao, Shuo Han, Aaron Carass, Xiang Li, Ari M. Blitz, Jerry L. Prince, Lotta Maria Ellingsen:
Shortcomings of Ventricle Segmentation Using Deep Convolutional Networks. 79-86 - Saeid Asgari Taghanaki, Arkadeep Das, Ghassan Hamarneh:
Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks. 87-94
First International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2018
- Noel C. F. Codella, Chung-Ching Lin, Allan Halpern, Michael Hind, Rogério Schmidt Feris, John R. Smith:
Collaborative Human-AI (CHAI): Evidence-Based Interpretable Melanoma Classification in Dermoscopic Images. 97-105 - Sérgio Pereira, Raphael Meier, Victor Alves, Mauricio Reyes, Carlos A. Silva:
Automatic Brain Tumor Grading from MRI Data Using Convolutional Neural Networks and Quality Assessment. 106-114 - Pieter Van Molle, Miguel De Strooper, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification. 115-123 - Mara Graziani, Vincent Andrearczyk, Henning Müller:
Regression Concept Vectors for Bidirectional Explanations in Histopathology. 124-132 - Wilson Silva, Kelwin Fernandes, Maria João Cardoso, Jaime S. Cardoso:
Towards Complementary Explanations Using Deep Neural Networks. 133-140 - Mahya Sadeghi, Parmit K. Chilana, M. Stella Atkins:
How Users Perceive Content-Based Image Retrieval for Identifying Skin Images. 141-148
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