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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 VIII

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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 14227)

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 (65 papers)

  1. Front Matter

    Pages i-xxxviii
    Download chapter PDF

  2. Clinical Applications – Neuroimaging

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation

      • Yicheng Wu, Zhonghua Wu, Hengcan Shi, Bjoern Picker, Winston Chong, Jianfei Cai
      Pages 3-13

    3. Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model

      • Wei Peng, Ehsan Adeli, Tomas Bosschieter, Sang Hyun Park, Qingyu Zhao, Kilian M. Pohl
      Pages 14-24

    4. Towards Accurate Microstructure Estimation via 3D Hybrid Graph Transformer

      • Junqing Yang, Haotian Jiang, Tewodros Tassew, Peng Sun, Jiquan Ma, Yong Xia et al.
      Pages 25-34

    5. Cortical Analysis of Heterogeneous Clinical Brain MRI Scans for Large-Scale Neuroimaging Studies

      • Karthik Gopinath, Douglas N. Greve, Sudeshna Das, Steve Arnold, Colin Magdamo, Juan Eugenio Iglesias
      Pages 35-45

    6. Flow-Based Geometric Interpolation of Fiber Orientation Distribution Functions

      • Xinyu Nie, Yonggang Shi
      Pages 46-55

    7. Learnable Subdivision Graph Neural Network for Functional Brain Network Analysis and Interpretable Cognitive Disorder Diagnosis

      • Dongdong Chen, Mengjun Liu, Zhenrong Shen, Xiangyu Zhao, Qian Wang, Lichi Zhang
      Pages 56-66

    8. FE-STGNN: Spatio-Temporal Graph Neural Network with Functional and Effective Connectivity Fusion for MCI Diagnosis

      • Dongdong Chen, Lichi Zhang
      Pages 67-76

    9. Learning Normal Asymmetry Representations for Homologous Brain Structures

      • Duilio Deangeli, Emmanuel Iarussi, Juan Pablo Princich, Mariana Bendersky, Ignacio Larrabide, José Ignacio Orlando
      Pages 77-87

    10. Simulation of Arbitrary Level Contrast Dose in MRI Using an Iterative Global Transformer Model

      • Dayang Wang, Srivathsa Pasumarthi, Greg Zaharchuk, Ryan Chamberlain
      Pages 88-98

    11. Development and Fast Transferring of General Connectivity-Based Diagnosis Model to New Brain Disorders with Adaptive Graph Meta-Learner

      • Yuxiao Liu, Mianxin Liu, Yuanwang Zhang, Dinggang Shen
      Pages 99-108

    12. Brain Anatomy-Guided MRI Analysis for Assessing Clinical Progression of Cognitive Impairment with Structural MRI

      • Lintao Zhang, Jinjian Wu, Lihong Wang, Li Wang, David C. Steffens, Shijun Qiu et al.
      Pages 109-119

    13. Dynamic Structural Brain Network Construction by Hierarchical Prototype Embedding GCN Using T1-MRI

      • Yilin Leng, Wenju Cui, Chen Bai, Zirui Chen, Yanyan Zheng, Jian Zheng
      Pages 120-130

    14. Microstructure Fingerprinting for Heterogeneously Oriented Tissue Microenvironments

      • Khoi Minh Huynh, Ye Wu, Sahar Ahmad, Pew-Thian Yap
      Pages 131-141

    15. AUA-dE: An Adaptive Uncertainty Guided Attention for Diffusion MRI Models Estimation

      • Tianshu Zheng, Ruicheng Ba, Xiaoli Wang, Chuyang Ye, Dan Wu
      Pages 142-151

    16. Relaxation-Diffusion Spectrum Imaging for Probing Tissue Microarchitecture

      • Ye Wu, Xiaoming Liu, Xinyuan Zhang, Khoi Minh Huynh, Sahar Ahmad, Pew-Thian Yap
      Pages 152-162

    17. Joint Representation of Functional and Structural Profiles for Identifying Common and Consistent 3-Hinge Gyral Folding Landmark

      • Shu Zhang, Ruoyang Wang, Yanqing Kang, Sigang Yu, Huawen Hu, Haiyang Zhang
      Pages 163-172

    18. Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations

      • Julian McGinnis, Suprosanna Shit, Hongwei Bran Li, Vasiliki Sideri-Lampretsa, Robert Graf, Maik Dannecker et al.
      Pages 173-183

    19. DeepSOZ: A Robust Deep Model for Joint Temporal and Spatial Seizure Onset Localization from Multichannel EEG Data

      • Deeksha M. Shama, Jiasen Jing, Archana Venkataraman
      Pages 184-194
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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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