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Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis

7th Joint International Workshop, CVII-STENT 2018 and Third International Workshop, LABELS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings

  • Conference proceedings
  • © 2018

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Editors:
  1. Danail Stoyanov

    1. University College London, London, UK

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  2. Zeike Taylor

    1. University of Leeds, Leeds, UK

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  3. Simone Balocco

    1. University of Barcelona, Barcelona, Spain

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  4. Raphael Sznitman

    1. University of Bern, Bern, Switzerland

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  5. Anne Martel

    1. Sunnybrook Health Science Centre, Toronto, Canada

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  6. Lena Maier-Hein

    1. German Cancer Research Center, Heidelberg, Germany

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  7. Luc Duong

    1. Ecole de Technologie Superieure, Montreal, Canada

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  8. Guillaume Zahnd

    1. Technical University of München, Garching, Germany

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  9. Stefanie Demirci

    1. Technical University Munich, Munich, Germany

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  10. Shadi Albarqouni

    1. Technical University of München, Garching, Germany

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  11. Su-Lin Lee

    1. Imperial College London, London, UK

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  12. Stefano Moriconi

    1. University College London, London, UK

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  13. Veronika Cheplygina

    1. Eindhoven University of Technology, Eindhoven, The Netherlands

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  14. Diana Mateus

    1. Technical University of Munich, Garching, Germany

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  15. Emanuele Trucco

    1. University of Dundee, Dundee, UK

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  16. Eric Granger

    1. École de Technologie Supérieure, Montréal, Canada

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  17. Pierre Jannin

    1. Universite de Rennes 1, Rennes, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11043)

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

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Table of contents (22 papers)

  1. Front Matter

    Pages I-XVII
    Download chapter PDF

  2. Proceedings of the 7th Joint MICCAI Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting (CVII-STENT 2018)

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Blood-Flow Estimation in the Hepatic Arteries Based on 3D/2D Angiography Registration

      • Simon Lessard, Rosalie Planteféve, François Michaud, Catherine Huet, Gilles Soulez, Samuel Kadoury
      Pages 3-10

    3. Automated Quantification of Blood Flow Velocity from Time-Resolved CT Angiography

      • Pieter Thomas Boonen, Nico Buls, Gert Van Gompel, Yannick De Brucker, Dimitri Aerden, Johan De Mey et al.
      Pages 11-18

    4. Multiple Device Segmentation for Fluoroscopic Imaging Using Multi-task Learning

      • Katharina Breininger, Tobias Würfl, Tanja Kurzendorfer, Shadi Albarqouni, Marcus Pfister, Markus Kowarschik et al.
      Pages 19-27

    5. Segmentation of the Aorta Using Active Contours with Histogram-Based Descriptors

      • Miguel Alemán-Flores, Daniel Santana-Cedrés, Luis Alvarez, Agustín Trujillo, Luis Gómez, Pablo G. Tahoces et al.
      Pages 28-35

    6. Layer Separation in X-ray Angiograms for Vessel Enhancement with Fully Convolutional Network

      • Haidong Hao, Hua Ma, Theo van Walsum
      Pages 36-44

    7. Generation of a HER2 Breast Cancer Gold-Standard Using Supervised Learning from Multiple Experts

      • Violeta Chang
      Pages 45-54

    8. Deep Learning-Based Detection and Segmentation for BVS Struts in IVOCT Images

      • Yihui Cao, Yifeng Lu, Qinhua Jin, Jing Jing, Yundai Chen, Jianan Li et al.
      Pages 55-63

    9. Towards Automatic Measurement of Type B Aortic Dissection Parameters: Methods, Applications and Perspective

      • Jianning Li, Long Cao, W. Cheng, M. Bowen, Wei Guo
      Pages 64-72

    10. Prediction of FFR from IVUS Images Using Machine Learning

      • Geena Kim, June-Goo Lee, Soo-Jin Kang, Paul Ngyuen, Do-Yoon Kang, Pil Hyung Lee et al.
      Pages 73-81

    11. Deep Learning Retinal Vessel Segmentation from a Single Annotated Example: An Application of Cyclic Generative Adversarial Neural Networks

      • Praneeth Sadda, John A. Onofrey, Xenophon Papademetris
      Pages 82-91

  3. Proceedings of the 3rd International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (LABELS 2018)

    1. Front Matter

      Pages 93-93
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    2. An Efficient and Comprehensive Labeling Tool for Large-Scale Annotation of Fundus Images

      • Jaemin Son, Sangkeun Kim, Sang Jun Park, Kyu-Hwan Jung
      Pages 95-104

    3. Crowd Disagreement About Medical Images Is Informative

      • Veronika Cheplygina, Josien P. W. Pluim
      Pages 105-111

    4. Imperfect Segmentation Labels: How Much Do They Matter?

      • Nicholas Heller, Joshua Dean, Nikolaos Papanikolopoulos
      Pages 112-120

    5. Crowdsourcing Annotation of Surgical Instruments in Videos of Cataract Surgery

      • Tae Soo Kim, Anand Malpani, Austin Reiter, Gregory D. Hager, Shameema Sikder, S. Swaroop Vedula
      Pages 121-130

    6. Four-Dimensional ASL MR Angiography Phantoms with Noise Learned by Neural Styling

      • Renzo Phellan, Thomas Linder, Michael Helle, Thiago V. Spina, Alexandre Falcão, Nils D. Forkert
      Pages 131-139

    7. Feature Learning Based on Visual Similarity Triplets in Medical Image Analysis: A Case Study of Emphysema in Chest CT Scans

      • Silas Nyboe Ørting, Jens Petersen, Veronika Cheplygina, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne
      Pages 140-149

    8. Capsule Networks Against Medical Imaging Data Challenges

      • Amelia Jiménez-Sánchez, Shadi Albarqouni, Diana Mateus
      Pages 150-160
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  1. Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis

Keywords

About this book

This book constitutes the refereed joint proceedings of the 7th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the Third International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018.
The 9 full papers presented at CVII-STENT 2017 and the 12 full papers presented at LABELS 2017 were carefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing.

Editors and Affiliations

  • University College London, London, UK

    Danail Stoyanov, Stefano Moriconi

  • University of Leeds, Leeds, UK

    Zeike Taylor

  • University of Barcelona, Barcelona, Spain

    Simone Balocco

  • University of Bern, Bern, Switzerland

    Raphael Sznitman

  • Sunnybrook Health Science Centre, Toronto, Canada

    Anne Martel

  • German Cancer Research Center, Heidelberg, Germany

    Lena Maier-Hein

  • Ecole de Technologie Superieure, Montreal, Canada

    Luc Duong

  • Technical University of München, Garching, Germany

    Guillaume Zahnd, Shadi Albarqouni

  • Technical University Munich, Munich, Germany

    Stefanie Demirci

  • Imperial College London, London, UK

    Su-Lin Lee

  • Eindhoven University of Technology, Eindhoven, The Netherlands

    Veronika Cheplygina

  • Technical University of Munich, Garching, Germany

    Diana Mateus

  • University of Dundee, Dundee, UK

    Emanuele Trucco

  • École de Technologie Supérieure, Montréal, Canada

    Eric Granger

  • Universite de Rennes 1, Rennes, France

    Pierre Jannin

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