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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 III

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Hayit Greenspan

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

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  2. Anant Madabhushi

    1. Emory University, Atlanta, USA

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  3. Parvin Mousavi

    1. Queen's University, Kingston, Canada

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  4. Septimiu Salcudean

    1. The University of British Columbia, Vancouver, Canada

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  5. James Duncan

    1. Yale University, New Haven, USA

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  6. Tanveer Syeda-Mahmood

    1. IBM Research, San Jose, USA

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  7. Russell Taylor

    1. Johns Hopkins University, Baltimore, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 14222)

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; clinical applications – 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.

Keywords

Table of contents (72 papers)

  1. Front Matter

    Pages i-xxxviii
    Download chapter PDF

  2. Machine Learning – Explainability, Bias, and Uncertainty II

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Pre-trained Diffusion Models for Plug-and-Play Medical Image Enhancement

      • Jun Ma, Yuanzhi Zhu, Chenyu You, Bo Wang
      Pages 3-13

    3. GRACE: A Generalized and Personalized Federated Learning Method for Medical Imaging

      • Ruipeng Zhang, Ziqing Fan, Qinwei Xu, Jiangchao Yao, Ya Zhang, Yanfeng Wang
      Pages 14-24

    4. Chest X-ray Image Classification: A Causal Perspective

      • Weizhi Nie, Chen Zhang, Dan Song, Yunpeng Bai, Keliang Xie, An-An Liu
      Pages 25-35

    5. DRMC: A Generalist Model with Dynamic Routing for Multi-center PET Image Synthesis

      • Zhiwen Yang, Yang Zhou, Hui Zhang, Bingzheng Wei, Yubo Fan, Yan Xu
      Pages 36-46

    6. Federated Condition Generalization on Low-dose CT Reconstruction via Cross-domain Learning

      • Shixuan Chen, Boxuan Cao, Yinda Du, Yaoduo Zhang, Ji He, Zhaoying Bian et al.
      Pages 47-56

    7. Enabling Geometry Aware Learning Through Differentiable Epipolar View Translation

      • Maximilian Rohleder, Charlotte Pradel, Fabian Wagner, Mareike Thies, Noah Maul, Felix Denzinger et al.
      Pages 57-65

    8. Enhance Early Diagnosis Accuracy of Alzheimer’s Disease by Elucidating Interactions Between Amyloid Cascade and Tau Propagation

      • Tingting Dan, Minjeong Kim, Won Hwa Kim, Guorong Wu
      Pages 66-76

    9. TauFlowNet: Uncovering Propagation Mechanism of Tau Aggregates by Neural Transport Equation

      • Tingting Dan, Minjeong Kim, Won Hwa Kim, Guorong Wu
      Pages 77-86

    10. Uncovering Structural-Functional Coupling Alterations for Neurodegenerative Diseases

      • Tingting Dan, Minjeong Kim, Won Hwa Kim, Guorong Wu
      Pages 87-96

    11. Toward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis

      • Ching-Hao Chiu, Hao-Wei Chung, Yu-Jen Chen, Yiyu Shi, Tsung-Yi Ho
      Pages 97-107

    12. Multi-Head Multi-Loss Model Calibration

      • Adrian Galdran, Johan W. Verjans, Gustavo Carneiro, Miguel A. González Ballester
      Pages 108-117

    13. Scale Federated Learning for Label Set Mismatch in Medical Image Classification

      • Zhipeng Deng, Luyang Luo, Hao Chen
      Pages 118-127

    14. Cross-Modulated Few-Shot Image Generation for Colorectal Tissue Classification

      • Amandeep Kumar, Ankan Kumar Bhunia, Sanath Narayan, Hisham Cholakkal, Rao Muhammad Anwer, Jorma Laaksonen et al.
      Pages 128-137

    15. Bidirectional Mapping with Contrastive Learning on Multimodal Neuroimaging Data

      • Kai Ye, Haoteng Tang, Siyuan Dai, Lei Guo, Johnny Yuehan Liu, Yalin Wang et al.
      Pages 138-148

    16. How Reliable are the Metrics Used for Assessing Reliability in Medical Imaging?

      • Mayank Gupta, Soumen Basu, Chetan Arora
      Pages 149-158

    17. Co-assistant Networks for Label Correction

      • Xuan Chen, Weiheng Fu, Tian Li, Xiaoshuang Shi, Hengtao Shen, Xiaofeng Zhu
      Pages 159-168

    18. M3D-NCA: Robust 3D Segmentation with Built-In Quality Control

      • John Kalkhof, Anirban Mukhopadhyay
      Pages 169-178

    19. The Role of Subgroup Separability in Group-Fair Medical Image Classification

      • Charles Jones, Mélanie Roschewitz, Ben Glocker
      Pages 179-188
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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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