Medical Image Computing and Computer Assisted Intervention – MICCAI 2021: 24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part III | SpringerLink
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Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

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

  • Conference proceedings
  • © 2021

Overview

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 12903)

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

Included in the following conference series:

Conference proceedings info: MICCAI 2021.

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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

Table of contents (60 papers)

  1. Front Matter

    Pages i-xxxvi
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  2. Machine Learning - Advances in Machine Learning Theory

    1. Front Matter

      Pages 1-1
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    2. Towards Robust General Medical Image Segmentation

      • Laura Daza, Juan C. Pérez, Pablo Arbeláez
      Pages 3-13

    3. Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation

      • Shuo Wang, Chen Qin, Nicolò Savioli, Chen Chen, Declan P. O’Regan, Stuart Cook et al.
      Pages 14-24

    4. Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-Tuning and Online-Learning

      • Junyu Chen, Evren Asma, Chung Chan
      Pages 25-35

    5. A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks

      • Qingsong Yao, Zecheng He, Yi Lin, Kai Ma, Yefeng Zheng, S. Kevin Zhou
      Pages 36-47

    6. Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation

      • Junjun He, Jin Ye, Cheng Li, Diping Song, Wanli Chen, Shanshan Wang et al.
      Pages 48-58

  3. Machine Learning - Attention Models

    1. Front Matter

      Pages 59-59
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    2. UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation

      • Yunhe Gao, Mu Zhou, Dimitris N. Metaxas
      Pages 61-71

    3. AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation

      • Di You, Fenglin Liu, Shen Ge, Xiaoxia Xie, Jing Zhang, Xian Wu
      Pages 72-82

    4. Continuous-Time Deep Glioma Growth Models

      • Jens Petersen, Fabian Isensee, Gregor Köhler, Paul F. Jäger, David Zimmerer, Ulf Neuberger et al.
      Pages 83-92

    5. Spine-Transformers: Vertebra Detection and Localization in Arbitrary Field-of-View Spine CT with Transformers

      • Rong Tao, Guoyan Zheng
      Pages 93-103

    6. Multi-view Analysis of Unregistered Medical Images Using Cross-View Transformers

      • Gijs van Tulder, Yao Tong, Elena Marchiori
      Pages 104-113

  4. Machine Learning - Domain Adaptation

    1. Front Matter

      Pages 115-115
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    2. Stain Mix-Up: Unsupervised Domain Generalization for Histopathology Images

      • Jia-Ren Chang, Min-Sheng Wu, Wei-Hsiang Yu, Chi-Chung Chen, Cheng-Kung Yang, Yen-Yu Lin et al.
      Pages 117-126

    3. A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation

      • Heran Yang, Jian Sun, Liwei Yang, Zongben Xu
      Pages 127-137

    4. Generative Self-training for Cross-Domain Unsupervised Tagged-to-Cine MRI Synthesis

      • Xiaofeng Liu, Fangxu Xing, Maureen Stone, Jiachen Zhuo, Timothy Reese, Jerry L. Prince et al.
      Pages 138-148

    5. Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation

      • Chen Chen, Kerstin Hammernik, Cheng Ouyang, Chen Qin, Wenjia Bai, Daniel Rueckert
      Pages 149-159

    6. Controllable Cardiac Synthesis via Disentangled Anatomy Arithmetic

      • Spyridon Thermos, Xiao Liu, Alison O’Neil, Sotirios A. Tsaftaris
      Pages 160-170

    7. CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation

      • Yutong Xie, Jianpeng Zhang, Chunhua Shen, Yong Xia
      Pages 171-180
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Other volumes

  1. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

  2. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

  3. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

  4. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

  5. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

  6. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

  7. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

  8. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

  9. Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis

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

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 III

  • 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/10.1007/978-3-030-87199-4

  • Publisher: Springer Cham

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

  • Copyright Information: Springer Nature Switzerland AG 2021

  • Softcover ISBN: 978-3-030-87198-7Published: 24 September 2021

  • eBook ISBN: 978-3-030-87199-4Published: 23 September 2021

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXXVI, 648

  • Number of Illustrations: 15 b/w illustrations, 185 illustrations in colour

  • Topics: Image Processing and Computer Vision, Artificial Intelligence, Pattern Recognition, Computational Biology/Bioinformatics, Health Informatics

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