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Medical Image Computing and Computer Assisted Intervention – MICCAI 2022

25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part V

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Linwei Wang

    1. Rochester Institute of Technology, Rochester, USA

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  2. Qi Dou

    1. Chinese University of Hong Kong, Hong Kong, Hong Kong

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  3. P. Thomas Fletcher

    1. University of Virginia, Charlottesville, USA

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  4. Stefanie Speidel

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

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  5. Shuo Li

    1. Case Western Reserve University, Cleveland, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13435)

Included in the following conference series:

Conference proceedings info: MICCAI 2022.

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Table of contents (69 papers)

  1. Front Matter

    Pages i-xl
    Download chapter PDF

  2. Image Segmentation II

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Automatic Segmentation of Hip Osteophytes in DXA Scans Using U-Nets

      • Raja Ebsim, Benjamin G. Faber, Fiona Saunders, Monika Frysz, Jenny Gregory, Nicholas C. Harvey et al.
      Pages 3-12

    3. CIRDataset: A Large-Scale Dataset for Clinically-Interpretable Lung Nodule Radiomics and Malignancy Prediction

      • Wookjin Choi, Navdeep Dahiya, Saad Nadeem
      Pages 13-22

    4. UNeXt: MLP-Based Rapid Medical Image Segmentation Network

      • Jeya Maria Jose Valanarasu, Vishal M. Patel
      Pages 23-33

    5. Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation

      • Yicheng Wu, Zhonghua Wu, Qianyi Wu, Zongyuan Ge, Jianfei Cai
      Pages 34-43

    6. Uncertainty-Guided Lung Nodule Segmentation with Feature-Aware Attention

      • Han Yang, Lu Shen, Mengke Zhang, Qiuli Wang
      Pages 44-54

    7. Thoracic Lymph Node Segmentation in CT Imaging via Lymph Node Station Stratification and Size Encoding

      • Dazhou Guo, Jia Ge, Ke Yan, Puyang Wang, Zhuotun Zhu, Dandan Zheng et al.
      Pages 55-65

    8. ACT: Semi-supervised Domain-Adaptive Medical Image Segmentation with Asymmetric Co-training

      • Xiaofeng Liu, Fangxu Xing, Nadya Shusharina, Ruth Lim, C.-C. Jay Kuo, Georges El Fakhri et al.
      Pages 66-76

    9. A Sense of Direction in Biomedical Neural Networks

      • Zewen Liu, Timothy F. Cootes
      Pages 77-86

    10. Stroke Lesion Segmentation from Low-Quality and Few-Shot MRIs via Similarity-Weighted Self-ensembling Framework

      • Dong Zhang, Raymond Confidence, Udunna Anazodo
      Pages 87-96

    11. Edge-Oriented Point-Cloud Transformer for 3D Intracranial Aneurysm Segmentation

      • Yifan Liu, Jie Liu, Yixuan Yuan
      Pages 97-106

    12. mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation

      • Yao Zhang, Nanjun He, Jiawei Yang, Yuexiang Li, Dong Wei, Yawen Huang et al.
      Pages 107-117

    13. Multimodal Brain Tumor Segmentation Using Contrastive Learning Based Feature Comparison with Monomodal Normal Brain Images

      • Huabing Liu, Dong Nie, Dinggang Shen, Jinda Wang, Zhenyu Tang
      Pages 118-127

    14. Meta-hallucinator: Towards Few-Shot Cross-Modality Cardiac Image Segmentation

      • Ziyuan Zhao, Fangcheng Zhou, Zeng Zeng, Cuntai Guan, S. Kevin Zhou
      Pages 128-139

    15. NestedFormer: Nested Modality-Aware Transformer for Brain Tumor Segmentation

      • Zhaohu Xing, Lequan Yu, Liang Wan, Tong Han, Lei Zhu
      Pages 140-150

    16. MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation

      • Chen Chen, Zeju Li, Cheng Ouyang, Matthew Sinclair, Wenjia Bai, Daniel Rueckert
      Pages 151-161

    17. A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation

      • Himashi Peiris, Munawar Hayat, Zhaolin Chen, Gary Egan, Mehrtash Harandi
      Pages 162-172

    18. Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models

      • Yizhe Zhang, Suraj Mishra, Peixian Liang, Hao Zheng, Danny Z. Chen
      Pages 173-182

    19. Modality-Adaptive Feature Interaction for Brain Tumor Segmentation with Missing Modalities

      • Zechen Zhao, Heran Yang, Jian Sun
      Pages 183-192
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Other volumes

  1. Medical Image Computing and Computer Assisted Intervention – MICCAI 2022

  2. Medical Image Computing and Computer Assisted Intervention – MICCAI 2022

  3. Medical Image Computing and Computer Assisted Intervention – MICCAI 2022

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  5. Medical Image Computing and Computer Assisted Intervention – MICCAI 2022

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  9. Computational Biomechanics for Medicine

  10. Computational Biomechanics for Medicine

Keywords

About this book

The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.
The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;

Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;

Part III: Breast imaging; colonoscopy; computer aided diagnosis;

Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;

Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;

Part VI: Image registration; image reconstruction;

Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization;

Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies.

 




Editors and Affiliations

  • Rochester Institute of Technology, Rochester, USA

    Linwei Wang

  • Chinese University of Hong Kong, Hong Kong, Hong Kong

    Qi Dou

  • University of Virginia, Charlottesville, USA

    P. Thomas Fletcher

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

    Stefanie Speidel

  • Case Western Reserve University, Cleveland, USA

    Shuo Li

Bibliographic Information

  • Book Title: Medical Image Computing and Computer Assisted Intervention – MICCAI 2022

  • Book Subtitle: 25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part V

  • Editors: Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-16443-9

  • Publisher: Springer Cham

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

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022

  • Softcover ISBN: 978-3-031-16442-2Published: 16 September 2022

  • eBook ISBN: 978-3-031-16443-9Published: 15 September 2022

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XL, 738

  • Number of Illustrations: 29 b/w illustrations, 224 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics, Signal, Image and Speech Processing, Machine Learning, Computer Applications

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