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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 IV

  • 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 14223)

Included in the following conference series:

Conference proceedings info: MICCAI 2023.

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Table of contents (75 papers)

  1. Front Matter

    Pages i-xxxviii
    Download chapter PDF

  2. Image Segmentation II

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Category-Level Regularized Unlabeled-to-Labeled Learning for Semi-supervised Prostate Segmentation with Multi-site Unlabeled Data

      • Zhe Xu, Donghuan Lu, Jiangpeng Yan, Jinghan Sun, Jie Luo, Dong Wei et al.
      Pages 3-13

    3. Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation

      • Shishuai Hu, Zehui Liao, Yong Xia
      Pages 14-23

    4. Transformer-Based Annotation Bias-Aware Medical Image Segmentation

      • Zehui Liao, Shishuai Hu, Yutong Xie, Yong Xia
      Pages 24-34

    5. Uncertainty-Informed Mutual Learning for Joint Medical Image Classification and Segmentation

      • Kai Ren, Ke Zou, Xianjie Liu, Yidi Chen, Xuedong Yuan, Xiaojing Shen et al.
      Pages 35-45

    6. A General Stitching Solution for Whole-Brain 3D Nuclei Instance Segmentation from Microscopy Images

      • Ziquan Wei, Tingting Dan, Jiaqi Ding, Mustafa Dere, Guorong Wu
      Pages 46-55

    7. Adult-Like Phase and Multi-scale Assistance for Isointense Infant Brain Tissue Segmentation

      • Jiameng Liu, Feihong Liu, Kaicong Sun, Mianxin Liu, Yuhang Sun, Yuyan Ge et al.
      Pages 56-66

    8. Robust Segmentation via Topology Violation Detection and Feature Synthesis

      • Liu Li, Qiang Ma, Cheng Ouyang, Zeju Li, Qingjie Meng, Weitong Zhang et al.
      Pages 67-77

    9. GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation

      • Ziyang Zheng, Jiewen Yang, Xinpeng Ding, Xiaowei Xu, Xiaomeng Li
      Pages 78-88

    10. Treasure in Distribution: A Domain Randomization Based Multi-source Domain Generalization for 2D Medical Image Segmentation

      • Ziyang Chen, Yongsheng Pan, Yiwen Ye, Hengfei Cui, Yong Xia
      Pages 89-99

    11. Diffusion Kinetic Model for Breast Cancer Segmentation in Incomplete DCE-MRI

      • Tianxu Lv, Yuan Liu, Kai Miao, Lihua Li, Xiang Pan
      Pages 100-109

    12. CAS-Net: Cross-View Aligned Segmentation by Graph Representation of Knees

      • Zixu Zhuang, Xin Wang, Sheng Wang, Zhenrong Shen, Xiangyu Zhao, Mengjun Liu et al.
      Pages 110-119

    13. One-Shot Traumatic Brain Segmentation with Adversarial Training and Uncertainty Rectification

      • Xiangyu Zhao, Zhenrong Shen, Dongdong Chen, Sheng Wang, Zixu Zhuang, Qian Wang et al.
      Pages 120-129

    14. MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain Generalization

      • Yuan Bi, Zhongliang Jiang, Ricarda Clarenbach, Reza Ghotbi, Angelos Karlas, Nassir Navab
      Pages 130-140

    15. M-GenSeg: Domain Adaptation for Target Modality Tumor Segmentation with Annotation-Efficient Supervision

      • Malo Alefsen, Eugene Vorontsov, Samuel Kadoury
      Pages 141-151

    16. Factor Space and Spectrum for Medical Hyperspectral Image Segmentation

      • Boxiang Yun, Qingli Li, Lubov Mitrofanova, Chunhua Zhou, Yan Wang
      Pages 152-162

    17. RBGNet: Reliable Boundary-Guided Segmentation of Choroidal Neovascularization

      • Tao Chen, Yitian Zhao, Lei Mou, Dan Zhang, Xiayu Xu, Mengting Liu et al.
      Pages 163-172

    18. QCResUNet: Joint Subject-Level and Voxel-Level Prediction of Segmentation Quality

      • Peijie Qiu, Satrajit Chakrabarty, Phuc Nguyen, Soumyendu Sekhar Ghosh, Aristeidis Sotiras
      Pages 173-182

    19. Consistency-Guided Meta-learning for Bootstrapping Semi-supervised Medical Image Segmentation

      • Qingyue Wei, Lequan Yu, Xianhang Li, Wei Shao, Cihang Xie, Lei Xing et al.
      Pages 183-193
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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. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops

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

  14. Deep Generative Models

  15. Myopic Maculopathy Analysis

Keywords

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.

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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