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Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

26th International Conference, Vancouver, BC, Canada, October 8–12, 2023, Proceedings, Part VI

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  • © 2023
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Editors:
  1. Hayit Greenspan

    1. Icahn School of Medicine, Mount Sinai, NYC, NY, USA, Tel Aviv University, Tel Aviv, Israel

  2. Anant Madabhushi

    1. Emory University, Atlanta, USA

  3. Parvin Mousavi

    1. Queen’s University, Kingston, Canada

  4. Septimiu Salcudean

    1. The University of British Columbia, Vancouver, Canada

  5. James Duncan

    1. Yale University, New Haven, USA

  6. Tanveer Syeda-Mahmood

    1. IBM Research, San Jose, USA

  7. Russell Taylor

    1. Johns Hopkins University, Baltimore, USA

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14225)

Included in the following conference series:

Conference proceedings info: MICCAI 2023.

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About this book

The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023.

The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections:

Part I: Machine learning with limited supervision and machine learning – transfer learning;

Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty;

Part III: Machine learning – explainability, bias and uncertainty; image segmentation;

Part IV: Image segmentation;

Part V: Computer-aided diagnosis;

Part VI: Computer-aided diagnosis; computational pathology;

Part VII: Clinical applications – abdomen; clinicalapplications – breast; clinical applications – cardiac; clinical applications – dermatology; clinical applications – fetal imaging; clinical applications – lung; clinical applications – musculoskeletal; clinical applications – oncology; clinical applications – ophthalmology; clinical applications – vascular;

Part VIII: Clinical applications – neuroimaging; microscopy;

Part IX: Image-guided intervention, surgical planning, and data science;

Part X: Image reconstruction and image registration.

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Table of contents (77 papers)

  1. Front Matter

    Pages i-xxxix
    Download chapter PDF

  2. Computer-Aided Diagnosis II

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Mining Negative Temporal Contexts for False Positive Suppression in Real-Time Ultrasound Lesion Detection

      • Haojun Yu, Youcheng Li, QuanLin Wu, Ziwei Zhao, Dengbo Chen, Dong Wang et al.
      Pages 3-13

    3. Combat Long-Tails in Medical Classification with Relation-Aware Consistency and Virtual Features Compensation

      • Li Pan, Yupei Zhang, Qiushi Yang, Tan Li, Zhen Chen
      Pages 14-23

    4. Towards Novel Class Discovery: A Study in Novel Skin Lesions Clustering

      • Wei Feng, Lie Ju, Lin Wang, Kaimin Song, Zongyuan Ge
      Pages 24-33

    5. Joint Segmentation and Sub-pixel Localization in Structured Light Laryngoscopy

      • Jann-Ole Henningson, Marion Semmler, Michael Döllinger, Marc Stamminger
      Pages 34-43

    6. A Style Transfer-Based Augmentation Framework for Improving Segmentation and Classification Performance Across Different Sources in Ultrasound Images

      • Bin Huang, Ziyue Xu, Shing-Chow Chan, Zhong Liu, Huiying Wen, Chao Hou et al.
      Pages 44-53

    7. HC-Net: Hybrid Classification Network for Automatic Periodontal Disease Diagnosis

      • Lanzhuju Mei, Yu Fang, Zhiming Cui, Ke Deng, Nizhuan Wang, Xuming He et al.
      Pages 54-63

    8. SegNetr: Rethinking the Local-Global Interactions and Skip Connections in U-Shaped Networks

      • Junlong Cheng, Chengrui Gao, Fengjie Wang, Min Zhu
      Pages 64-74

    9. Gradient and Feature Conformity-Steered Medical Image Classification with Noisy Labels

      • Xiaohan Xing, Zhen Chen, Zhifan Gao, Yixuan Yuan
      Pages 75-84

    10. Multi-modality Contrastive Learning for Sarcopenia Screening from Hip X-rays and Clinical Information

      • Qiangguo Jin, Changjiang Zou, Hui Cui, Changming Sun, Shu-Wei Huang, Yi-Jie Kuo et al.
      Pages 85-94

    11. DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification

      • Yijun Yang, Huazhu Fu, Angelica I. Aviles-Rivero, Carola-Bibiane Schönlieb, Lei Zhu
      Pages 95-105

    12. Whole-Heart Reconstruction with Explicit Topology Integrated Learning

      • Huilin Yang, Roger Tam, Xiaoying Tang
      Pages 106-115

    13. Enhancing Automatic Placenta Analysis Through Distributional Feature Recomposition in Vision-Language Contrastive Learning

      • Yimu Pan, Tongan Cai, Manas Mehta, Alison D. Gernand, Jeffery A. Goldstein, Leena Mithal et al.
      Pages 116-126

    14. Frequency-Mixed Single-Source Domain Generalization for Medical Image Segmentation

      • Heng Li, Haojin Li, Wei Zhao, Huazhu Fu, Xiuyun Su, Yan Hu et al.
      Pages 127-136

    15. A Semantic-Guided and Knowledge-Based Generative Framework for Orthodontic Visual Outcome Preview

      • Yizhou Chen, Xiaojun Chen
      Pages 137-147

    16. A Multi-task Method for Immunofixation Electrophoresis Image Classification

      • Yi Shi, Rui-Xiang Li, Wen-Qi Shao, Xin-Cen Duan, Han-Jia Ye, De-Chuan Zhan et al.
      Pages 148-158

    17. Thinking Like Sonographers: A Deep CNN Model for Diagnosing Gout from Musculoskeletal Ultrasound

      • Zhi Cao, Weijing Zhang, Keke Chen, Di Zhao, Daoqiang Zhang, Hongen Liao et al.
      Pages 159-168

    18. Thyroid Nodule Diagnosis in Dynamic Contrast-Enhanced Ultrasound via Microvessel Infiltration Awareness

      • Haojie Han, Hongen Liao, Daoqiang Zhang, Wentao Kong, Fang Chen
      Pages 169-179

    19. Polar Eyeball Shape Net for 3D Posterior Ocular Shape Representation

      • Jiaqi Zhang, Yan Hu, Xiaojuan Qi, Ting Meng, Lihui Wang, Huazhu Fu et al.
      Pages 180-190
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Other volumes

  1. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  2. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  3. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  4. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  5. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  6. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  7. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  8. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  9. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  10. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

  11. Graphs in Biomedical Image Analysis, and Overlapped Cell on Tissue Dataset for Histopathology

  12. Data Augmentation, Labelling, and Imperfections

  13. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops

  14. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops

  15. Deep Generative Models

  16. Myopic Maculopathy Analysis

  17. Computational Biomechanics for Medicine

Editors and Affiliations

  • Icahn School of Medicine, Mount Sinai, NYC, NY, USA, Tel Aviv University, Tel Aviv, Israel

    Hayit Greenspan

  • Emory University, Atlanta, USA

    Anant Madabhushi

  • Queen’s University, Kingston, Canada

    Parvin Mousavi

  • The University of British Columbia, Vancouver, Canada

    Septimiu Salcudean

  • Yale University, New Haven, USA

    James Duncan

  • IBM Research, San Jose, USA

    Tanveer Syeda-Mahmood

  • Johns Hopkins University, Baltimore, USA

    Russell Taylor

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