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  • Conference proceedings
  • © 2018

Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part II

Editors:

  1. Alejandro F. Frangi

    1. University of Leeds, Leeds, UK

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  2. Julia A. Schnabel

    1. King’s College London, London, UK

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  3. Christos Davatzikos

    1. University of Pennsylvania, Philadelphia, USA

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  4. Carlos Alberola-López

    1. Universidad de Valladolid, Valladolid, Spain

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  5. Gabor Fichtinger

    1. Queen’s University, Kingston, Canada

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11071)

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

Conference series link(s): MICCAI: International Conference on Medical Image Computing and Computer-Assisted Intervention

Conference proceedings info: MICCAI 2019.

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Table of contents (106 papers)

  1. Optical and Histology Applications: Histology Applications

    1. Invasive Cancer Detection Utilizing Compressed Convolutional Neural Network and Transfer Learning

      • Bin Kong, Shanhui Sun, Xin Wang, Qi Song, Shaoting Zhang
      Pages 156-164

    2. Which Way Round? A Study on the Performance of Stain-Translation for Segmenting Arbitrarily Dyed Histological Images

      • Michael Gadermayr, Vitus Appel, Barbara M. Klinkhammer, Peter Boor, Dorit Merhof
      Pages 165-173

    3. Graph CNN for Survival Analysis on Whole Slide Pathological Images

      • Ruoyu Li, Jiawen Yao, Xinliang Zhu, Yeqing Li, Junzhou Huang
      Pages 174-182

    4. Fully Automated Blind Color Deconvolution of Histopathological Images

      • Natalia Hidalgo-Gavira, Javier Mateos, Miguel Vega, Rafael Molina, Aggelos K. Katsaggelos
      Pages 183-191

    5. Improving Whole Slide Segmentation Through Visual Context - A Systematic Study

      • Korsuk Sirinukunwattana, Nasullah Khalid Alham, Clare Verrill, Jens Rittscher
      Pages 192-200

    6. Adversarial Domain Adaptation for Classification of Prostate Histopathology Whole-Slide Images

      • Jian Ren, Ilker Hacihaliloglu, Eric A. Singer, David J. Foran, Xin Qi
      Pages 201-209

    7. Rotation Equivariant CNNs for Digital Pathology

      • Bastiaan S. Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, Max Welling
      Pages 210-218

    8. A Probabilistic Model Combining Deep Learning and Multi-atlas Segmentation for Semi-automated Labelling of Histology

      • Alessia Atzeni, Marnix Jansen, Sébastien Ourselin, Juan Eugenio Iglesias
      Pages 219-227

    9. BESNet: Boundary-Enhanced Segmentation of Cells in Histopathological Images

      • Hirohisa Oda, Holger R. Roth, Kosuke Chiba, Jure Sokolić, Takayuki Kitasaka, Masahiro Oda et al.
      Pages 228-236

    10. Panoptic Segmentation with an End-to-End Cell R-CNN for Pathology Image Analysis

      • Donghao Zhang, Yang Song, Dongnan Liu, Haozhe Jia, Siqi Liu, Yong Xia et al.
      Pages 237-244

    11. Integration of Spatial Distribution in Imaging-Genetics

      • Vaishnavi Subramanian, Weizhao Tang, Benjamin Chidester, Jian Ma, Minh N. Do
      Pages 245-253

    12. Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology

      • Heather D. Couture, J. S. Marron, Charles M. Perou, Melissa A. Troester, Marc Niethammer
      Pages 254-262

  2. Optical and Histology Applications: Microscopy Applications

    1. Front Matter

      Pages 263-263
      PDF

    2. Cell Detection with Star-Convex Polygons

      • Uwe Schmidt, Martin Weigert, Coleman Broaddus, Gene Myers
      Pages 265-273

    3. Deep Convolutional Gaussian Mixture Model for Stain-Color Normalization of Histopathological Images

      • Farhad Ghazvinian Zanjani, Svitlana Zinger, Peter H. N. de With
      Pages 274-282

    4. Learning to Segment 3D Linear Structures Using Only 2D Annotations

      • Mateusz Koziński, Agata Mosinska, Mathieu Salzmann, Pascal Fua
      Pages 283-291

    5. A Multiresolution Convolutional Neural Network with Partial Label Training for Annotating Reflectance Confocal Microscopy Images of Skin

      • Alican Bozkurt, Kivanc Kose, Christi Alessi-Fox, Melissa Gill, Jennifer Dy, Dana Brooks et al.
      Pages 292-299

    6. Weakly-Supervised Learning-Based Feature Localization for Confocal Laser Endomicroscopy Glioma Images

      • Mohammadhassan Izadyyazdanabadi, Evgenii Belykh, Claudio Cavallo, Xiaochun Zhao, Sirin Gandhi, Leandro Borba Moreira et al.
      Pages 300-308

    7. Synaptic Partner Prediction from Point Annotations in Insect Brains

      • Julia Buhmann, Renate Krause, Rodrigo Ceballos Lentini, Nils Eckstein, Matthew Cook, Srinivas Turaga et al.
      Pages 309-316

    8. Synaptic Cleft Segmentation in Non-isotropic Volume Electron Microscopy of the Complete Drosophila Brain

      • Larissa Heinrich, Jan Funke, Constantin Pape, Juan Nunez-Iglesias, Stephan Saalfeld
      Pages 317-325
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Other Volumes

  1. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

  2. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

  3. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

  4. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

  5. Computational Biomechanics for Medicine

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About this book

The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018.

The 373 revised full papers presented were carefully reviewed and selected from 1068 submissions in a double-blind review process. The papers have been organized in the following topical sections:
Part I: Image Quality and Artefacts; Image Reconstruction Methods; Machine Learning in Medical Imaging; Statistical Analysis for Medical Imaging; Image Registration Methods.
Part II: Optical and Histology Applications: Optical Imaging Applications; Histology Applications; Microscopy Applications; Optical Coherence Tomography and Other Optical Imaging Applications. Cardiac, Chest and Abdominal Applications: Cardiac Imaging Applications: Colorectal, Kidney and Liver Imaging Applications; Lung Imaging Applications; Breast Imaging Applications; Other Abdominal Applications.
Part III: Diffusion Tensor Imaging and Functional MRI: Diffusion Tensor Imaging; Diffusion Weighted Imaging; Functional MRI; Human Connectome. Neuroimaging and Brain Segmentation Methods: Neuroimaging; Brain Segmentation Methods.
Part IV: Computer Assisted Intervention: Image Guided Interventions and Surgery; Surgical Planning, Simulation and Work Flow Analysis; Visualization and Augmented Reality. Image Segmentation Methods: General Image Segmentation Methods, Measures and Applications; Multi-Organ Segmentation; Abdominal Segmentation Methods; Cardiac Segmentation Methods; Chest, Lung and Spine Segmentation; Other Segmentation Applications. 

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Keywords

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Editors and Affiliations

  • University of Leeds, Leeds, UK

    Alejandro F. Frangi

  • King’s College London, London, UK

    Julia A. Schnabel

  • University of Pennsylvania, Philadelphia, USA

    Christos Davatzikos

  • Universidad de Valladolid, Valladolid, Spain

    Carlos Alberola-López

  • Queen’s University, Kingston, Canada

    Gabor Fichtinger

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Bibliographic Information

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Buy it now

eBook USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

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