Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017

1. Front Matter

   Pages I-XXVIII

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2. Optical Imaging

   1. Front Matter

      Pages 1-1

      PDF

   2. Cell Lineage Tracing in Lens-Free Microscopy Videos

      • Markus Rempfler, Sanjeev Kumar, Valentin Stierle, Philipp Paulitschke, Bjoern Andres, Bjoern H. Menze

      Pages 3-11

   3. Separation of Transmitted Light and Scattering Components in Transmitted Microscopy

      • Mihoko Shimano, Ryoma Bise, Yinqiang Zheng, Imari Sato

      Pages 12-20

   4. Neuron Segmentation Using Deep Complete Bipartite Networks

      • Jianxu Chen, Sreya Banerjee, Abhinav Grama, Walter J. Scheirer, Danny Z. Chen

      Pages 21-29

   5. Cell Encoding for Histopathology Image Classification

      • Xiaoshuang Shi, Fuyong Xing, Yuanpu Xie, Hai Su, Lin Yang

      Pages 30-38

   6. Endoscopic Depth Measurement and Super-Spectral-Resolution Imaging

      • Jianyu Lin, Neil T. Clancy, Yang Hu, Ji Qi, Taran Tatla, Danail Stoyanov et al.

      Pages 39-47

   7. Computational Immunohistochemistry: Recipes for Standardization of Immunostaining

      • Nuri Murat Arar, Pushpak Pati, Aditya Kashyap, Anna Fomitcheva Khartchenko, Orcun Goksel, Govind V. Kaigala et al.

      Pages 48-55

   8. Two-Stream Bidirectional Long Short-Term Memory for Mitosis Event Detection and Stage Localization in Phase-Contrast Microscopy Images

      • Yunxiang Mao, Zhaozheng Yin

      Pages 56-64

   9. Refocusing Phase Contrast Microscopy Images

      • Liang Han, Zhaozheng Yin

      Pages 65-74

   10. Semi-supervised Segmentation of Optic Cup in Retinal Fundus Images Using Variational Autoencoder

       • Suman Sedai, Dwarikanath Mahapatra, Sajini Hewavitharanage, Stefan Maetschke, Rahil Garnavi

       Pages 75-82

   11. QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data

       • Franziska Schirrmacher, Thomas Köhler, Lennart Husvogt, James G. Fujimoto, Joachim Hornegger, Andreas K. Maier

       Pages 83-91

   12. Fast Background Removal Method for 3D Multi-channel Deep Tissue Fluorescence Imaging

       • Chenchen Li, Xiaowei Li, Hongji Cao, He Jiang, Xiaotie Deng, Danny Z. Chen et al.

       Pages 92-99

   13. Fast Estimation of Haemoglobin Concentration in Tissue Via Wavelet Decomposition

       • Geoffrey Jones, Neil T. Clancy, Xiaofei Du, Maria Robu, Simon Arridge, Daniel S. Elson et al.

       Pages 100-108

   14. Efficient Reconstruction of Holographic Lens-Free Images by Sparse Phase Recovery

       • Benjamin D. Haeffele, Richard Stahl, Geert Vanmeerbeeck, René Vidal

       Pages 109-117

   15. Quality Assessment of Retinal Hyperspectral Images Using SURF and Intensity Features

       • Faten M’hiri, Claudia Chevrefils, Jean-Philippe Sylvestre

       Pages 118-125

   16. Isotropic Reconstruction of 3D Fluorescence Microscopy Images Using Convolutional Neural Networks

       • Martin Weigert, Loic Royer, Florian Jug, Gene Myers

       Pages 126-134

   17. Deep Learning for Isotropic Super-Resolution from Non-isotropic 3D Electron Microscopy

       • Larissa Heinrich, John A. Bogovic, Stephan Saalfeld

       Pages 135-143

   18. Histological Detection of High-Risk Benign Breast Lesions from Whole Slide Images

       • Akif Burak Tosun, Luong Nguyen, Nathan Ong, Olga Navolotskaia, Gloria Carter, Jeffrey L. Fine et al.

       Pages 144-152

   19. Accurate Correspondence of Cone Photoreceptor Neurons in the Human Eye Using Graph Matching Applied to Longitudinal Adaptive Optics Images

       • Jianfei Liu, HaeWon Jung, Johnny Tam

       Pages 153-161

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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