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  • Conference proceedings
  • © 2021

Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part II

Editors:

  1. Marleen de Bruijne

    1. Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands

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  2. Philippe C. Cattin

    1. University of Basel, Allschwil, Switzerland

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  3. Stéphane Cotin

    1. Inria Nancy Grand Est, Villers-lès-Nancy, France

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  4. Nicolas Padoy

    1. ICube, Université de Strasbourg, CNRS, Strasbourg, France

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  5. Stefanie Speidel

    1. National Center for Tumor Diseases (NCT/UCC), Dresden, Germany

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  6. Yefeng Zheng

    1. Tencent Jarvis Lab, Shenzhen, China

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  7. Caroline Essert

    1. ICube, Université de Strasbourg, CNRS, Strasbourg, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12902)

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 2021.

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Table of contents (60 papers)

  1. Front Matter

    Pages i-xxxvii
    PDF

  2. Machine Learning - Self-Supervised Learning

    1. Front Matter

      Pages 1-1
      PDF

    3. Segmentation of Left Atrial MR Images via Self-supervised Semi-supervised Meta-learning

      • Dani Kiyasseh, Albert Swiston, Ronghua Chen, Antong Chen
      Pages 13-24

    4. Deformed2Self: Self-supervised Denoising for Dynamic Medical Imaging

      • Junshen Xu, Elfar Adalsteinsson
      Pages 25-35

    5. Imbalance-Aware Self-supervised Learning for 3D Radiomic Representations

      • Hongwei Li, Fei-Fei Xue, Krishna Chaitanya, Shengda Luo, Ivan Ezhov, Benedikt Wiestler et al.
      Pages 36-46

    6. Self-supervised Visual Representation Learning for Histopathological Images

      • Pengshuai Yang, Zhiwei Hong, Xiaoxu Yin, Chengzhan Zhu, Rui Jiang
      Pages 47-57

    7. Contrastive Learning with Continuous Proxy Meta-data for 3D MRI Classification

      • Benoit Dufumier, Pietro Gori, Julie Victor, Antoine Grigis, Michele Wessa, Paolo Brambilla et al.
      Pages 58-68

    8. Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-supervised Learning

      • Pak-Hei Yeung, Ana I. L. Namburete, Weidi Xie
      Pages 69-79

    9. Self-supervised Longitudinal Neighbourhood Embedding

      • Jiahong Ouyang, Qingyu Zhao, Ehsan Adeli, Edith V. Sullivan, Adolf Pfefferbaum, Greg Zaharchuk et al.
      Pages 80-89

    10. Self-supervised Multi-modal Alignment for Whole Body Medical Imaging

      • Rhydian Windsor, Amir Jamaludin, Timor Kadir, Andrew Zisserman
      Pages 90-101

    11. SimTriplet: Simple Triplet Representation Learning with a Single GPU

      • Quan Liu, Peter C. Louis, Yuzhe Lu, Aadarsh Jha, Mengyang Zhao, Ruining Deng et al.
      Pages 102-112

    12. Lesion-Based Contrastive Learning for Diabetic Retinopathy Grading from Fundus Images

      • Yijin Huang, Li Lin, Pujin Cheng, Junyan Lyu, Xiaoying Tang
      Pages 113-123

    13. SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation

      • Xiaoman Zhang, Shixiang Feng, Yuhang Zhou, Ya Zhang, Yanfeng Wang
      Pages 124-133

    14. Self-supervised Correction Learning for Semi-supervised Biomedical Image Segmentation

      • Ruifei Zhang, Sishuo Liu, Yizhou Yu, Guanbin Li
      Pages 134-144

    16. Contrastive Learning of Relative Position Regression for One-Shot Object Localization in 3D Medical Images

      • Wenhui Lei, Wei Xu, Ran Gu, Hao Fu, Shaoting Zhang, Shichuan Zhang et al.
      Pages 155-165

    17. Topological Learning and Its Application to Multimodal Brain Network Integration

      • Tananun Songdechakraiwut, Li Shen, Moo Chung
      Pages 166-176

    18. One-Shot Medical Landmark Detection

      • Qingsong Yao, Quan Quan, Li Xiao, S. Kevin Zhou
      Pages 177-188

    19. Implicit Field Learning for Unsupervised Anomaly Detection in Medical Images

      • Sergio Naval Marimont, Giacomo Tarroni
      Pages 189-198
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Other Volumes

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About this book

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.*

The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: image segmentation

Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning

Part III: machine learning - advances in machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty

Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality

Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction

Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular

Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging – others; and clinical applications - oncology

Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound

*The conference was held virtually.

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Keywords

  • artificial intelligence
  • bioinformatics
  • computer aided diagnosis
  • computer assisted interventions
  • computer vision
  • data mining
  • image analysis
  • image matching
  • image processing
  • image quality
  • image reconstruction
  • image segmentation
  • imaging systems
  • machine learning
  • medical images
  • neural networks
  • object recognition
  • pattern recognition
  • segmentation methods
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Editors and Affiliations

  • Erasmus MC - University Medical Center Rotterdam, Rotterdam, The Netherlands

    Marleen de Bruijne

  • University of Basel, Allschwil, Switzerland

    Philippe C. Cattin

  • Inria Nancy Grand Est, Villers-lès-Nancy, France

    Stéphane Cotin

  • ICube, Université de Strasbourg, CNRS, Strasbourg, France

    Nicolas Padoy, Caroline Essert

  • National Center for Tumor Diseases (NCT/UCC), Dresden, Germany

    Stefanie Speidel

  • Tencent Jarvis Lab, Shenzhen, China

    Yefeng Zheng

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Bibliographic Information

  • Book Title: Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

  • Book Subtitle: 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part II

  • Editors: Marleen de Bruijne, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-87196-3

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2021

  • Softcover ISBN: 978-3-030-87195-6Published: 24 September 2021

  • eBook ISBN: 978-3-030-87196-3Published: 23 September 2021

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXXVII, 662

  • Number of Illustrations: 6 b/w illustrations, 175 illustrations in colour

  • Topics: Computer Vision, Artificial Intelligence, Automated Pattern Recognition, Computational and Systems Biology, Health Informatics

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Access via your institution
eBook USD 84.99
Price excludes VAT (USA)
  • ISBN: 978-3-030-87196-3
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 109.99
Price excludes VAT (USA)
Learn about institutional subscriptions