Medical Image Computing and Computer Assisted Intervention − MICCAI 2017

1. Front Matter

   Pages I-XXVI

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2. Feature Extraction and Classification Techniques

   1. Front Matter

      Pages 1-1

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   2. Deep Multi-task Multi-channel Learning for Joint Classification and Regression of Brain Status

      • Mingxia Liu, Jun Zhang, Ehsan Adeli, Dinggang Shen

      Pages 3-11

   3. Nonlinear Feature Space Transformation to Improve the Prediction of MCI to AD Conversion

      • Pin Zhang, Bibo Shi, Charles D. Smith, Jundong Liu

      Pages 12-20

   4. Kernel Generalized-Gaussian Mixture Model for Robust Abnormality Detection

      • Nitin Kumar, Ajit V. Rajwade, Sharat Chandran, Suyash P. Awate

      Pages 21-29

   5. Latent Processes Governing Neuroanatomical Change in Aging and Dementia

      • Christian Wachinger, Anna Rieckmann, Martin Reuter

      Pages 30-37

   6. A Multi-armed Bandit to Smartly Select a Training Set from Big Medical Data

      • Benjamín Gutiérrez, Loïc Peter, Tassilo Klein, Christian Wachinger

      Pages 38-45

   7. Multi-level Multi-task Structured Sparse Learning for Diagnosis of Schizophrenia Disease

      • Mingliang Wang, Xiaoke Hao, Jiashuang Huang, Kangcheng Wang, Xijia Xu, Daoqiang Zhang

      Pages 46-54

   8. An Unbiased Penalty for Sparse Classification with Application to Neuroimaging Data

      • Li Zhang, Dana Cobzas, Alan Wilman, Linglong Kong

      Pages 55-63

   9. Unsupervised Feature Learning for Endomicroscopy Image Retrieval

      • Yun Gu, Khushi Vyas, Jie Yang, Guang-Zhong Yang

      Pages 64-71

   10. Maximum Mean Discrepancy Based Multiple Kernel Learning for Incomplete Multimodality Neuroimaging Data

       • Xiaofeng Zhu, Kim-Han Thung, Ehsan Adeli, Yu Zhang, Dinggang Shen

       Pages 72-80

   11. Liver Tissue Classification in Patients with Hepatocellular Carcinoma by Fusing Structured and Rotationally Invariant Context Representation

       • John Treilhard, Susanne Smolka, Lawrence Staib, Julius Chapiro, MingDe Lin, Georgy Shakirin et al.

       Pages 81-88

   12. DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRI

       • Yawen Huang, Ling Shao, Alejandro F. Frangi

       Pages 89-98

   13. Supervised Intra-embedding of Fisher Vectors for Histopathology Image Classification

       • Yang Song, Hang Chang, Heng Huang, Weidong Cai

       Pages 99-106

   14. GSplit LBI: Taming the Procedural Bias in Neuroimaging for Disease Prediction

       • Xinwei Sun, Lingjing Hu, Yuan Yao, Yizhou Wang

       Pages 107-115

   15. MRI-Based Surgical Planning for Lumbar Spinal Stenosis

       • Gabriele Abbati, Stefan Bauer, Sebastian Winklhofer, Peter J. Schüffler, Ulrike Held, Jakob M. Burgstaller et al.

       Pages 116-124

   16. Pattern Visualization and Recognition Using Tensor Factorization for Early Differential Diagnosis of Parkinsonism

       • Rui Li, Ping Wu, Igor Yakushev, Jian Wang, Sibylle I. Ziegler, Stefan Förster et al.

       Pages 125-133

   17. Physiological Parameter Estimation from Multispectral Images Unleashed

       • Sebastian J. Wirkert, Anant S. Vemuri, Hannes G. Kenngott, Sara Moccia, Michael Götz, Benjamin F. B. Mayer et al.

       Pages 134-141

   18. Segmentation of Cortical and Subcortical Multiple Sclerosis Lesions Based on Constrained Partial Volume Modeling

       • Mário João Fartaria, Alexis Roche, Reto Meuli, Cristina Granziera, Tobias Kober, Meritxell Bach Cuadra

       Pages 142-149

   19. Classification of Pancreatic Cysts in Computed Tomography Images Using a Random Forest and Convolutional Neural Network Ensemble

       • Konstantin Dmitriev, Arie E. Kaufman, Ammar A. Javed, Ralph H. Hruban, Elliot K. Fishman, Anne Marie Lennon et al.

       Pages 150-158

The three-volume set LNCS 10433, 10434, and 10435 constitutes the refereed proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, held inQuebec City, Canada, in September 2017.

The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process. The papers have been organized in the following topical sections: Part I: atlas and surface-based techniques; shape and patch-based techniques; registration techniques, functional imaging, connectivity, and brain parcellation; diffusion magnetic resonance imaging (dMRI) and tensor/fiber processing; and image segmentation and modelling. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical interventions; interventional imaging and navigation; and medical image computing. Part III: feature extraction and classification techniques;and machine learning in medical image computing.

• artificial intelligence
• computer vision
• estimation
• face recognition
• image analysis
• image processing
• image quality
• image reconstruction
• image registration
• image segmentation
• learning algorithms
• machine learning
• medical images
• motion estimation
• neural networks
• probability
• reconstruction
• segmentation methods
• signal processing
• Support Vector Machines (SVM)

• Université de Sherbrooke, Sherbrooke, Canada

  Maxime Descoteaux

• DKFZ, Heidelberg, Germany

  Lena Maier-Hein

• Ulm University of Applied Sciences, Ulm, Germany

  Alfred Franz

• Université de Rennes 1, Rennes, France

  Pierre Jannin

• McGill University, Montreal, Canada

  D. Louis Collins

• Université Laval, Québec, Canada

  Simon Duchesne

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