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Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part II

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Anne L. Martel

    1. University of Toronto, Toronto, Canada

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  2. Purang Abolmaesumi

    1. The University of British Columbia, Vancouver, Canada

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  3. Danail Stoyanov

    1. University College London, London, UK

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  4. Diana Mateus

    1. École Centrale de Nantes, Nantes, France

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  5. Maria A. Zuluaga

    1. EURECOM, Biot, France

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  6. S. Kevin Zhou

    1. Chinese Academy of Sciences, Beijing, China

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  7. Daniel Racoceanu

    1. Sorbonne University, Paris, France

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  8. Leo Joskowicz

    1. The Hebrew University of Jerusalem, Jerusalem, Israel

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12262)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: MICCAI 2020.

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Table of contents (75 papers)

  1. Cross-Domain Methods and Reconstruction

    1. Cross-domain Medical Image Translation by Shared Latent Gaussian Mixture Model

      • Yingying Zhu, Youbao Tang, Yuxing Tang, Daniel C. Elton, Sungwon Lee, Perry J. Pickhardt et al.
      Pages 379-389

    2. Self-supervised Skull Reconstruction in Brain CT Images with Decompressive Craniectomy

      • Franco Matzkin, Virginia Newcombe, Susan Stevenson, Aneesh Khetani, Tom Newman, Richard Digby et al.
      Pages 390-399

    3. X2Teeth: 3D Teeth Reconstruction from a Single Panoramic Radiograph

      • Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang, Lei He
      Pages 400-409

    4. Domain Adaptation for Ultrasound Beamforming

      • Jaime Tierney, Adam Luchies, Christopher Khan, Brett Byram, Matthew Berger
      Pages 410-420

    5. CDF-Net: Cross-Domain Fusion Network for Accelerated MRI Reconstruction

      • Osvald Nitski, Sayan Nag, Chris McIntosh, Bo Wang
      Pages 421-430

  2. Domain Adaptation

    1. Front Matter

      Pages 431-431
      Download chapter PDF

    2. Improve Unseen Domain Generalization via Enhanced Local Color Transformation

      • Jianhao Xiong, Andre Wang He, Meng Fu, Xinyue Hu, Yifan Zhang, Congxin Liu et al.
      Pages 433-443

    3. Transport-Based Joint Distribution Alignment for Multi-site Autism Spectrum Disorder Diagnosis Using Resting-State fMRI

      • Junyi Zhang, Peng Wan, Daoqiang Zhang
      Pages 444-453

    4. Automatic and Interpretable Model for Periodontitis Diagnosis in Panoramic Radiographs

      • Haoyang Li, Juexiao Zhou, Yi Zhou, Jieyu Chen, Feng Gao, Ying Xu et al.
      Pages 454-463

    5. Residual-CycleGAN Based Camera Adaptation for Robust Diabetic Retinopathy Screening

      • Dalu Yang, Yehui Yang, Tiantian Huang, Binghong Wu, Lei Wang, Yanwu Xu
      Pages 464-474

    6. Shape-Aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains

      • Quande Liu, Qi Dou, Pheng-Ann Heng
      Pages 475-485

    7. Automatic Plane Adjustment of Orthopedic Intraoperative Flat Panel Detector CT-Volumes

      • Celia Martín Vicario, Florian Kordon, Felix Denzinger, Markus Weiten, Sarina Thomas, Lisa Kausch et al.
      Pages 486-495

    8. Unsupervised Graph Domain Adaptation for Neurodevelopmental Disorders Diagnosis

      • Bomin Wang, Zhi Liu, Yujun Li, Xiaoyan Xiao, Ranran Zhang, Yankun Cao et al.
      Pages 496-505

    9. JBFnet - Low Dose CT Denoising by Trainable Joint Bilateral Filtering

      • Mayank Patwari, Ralf Gutjahr, Rainer Raupach, Andreas Maier
      Pages 506-515

    10. MI\(^2\)GAN: Generative Adversarial Network for Medical Image Domain Adaptation Using Mutual Information Constraint

      • Xinpeng Xie, Jiawei Chen, Yuexiang Li, Linlin Shen, Kai Ma, Yefeng Zheng
      Pages 516-525

  3. Machine Learning Applications

    1. Front Matter

      Pages 527-527
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    2. Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment

      • Geeticka Chauhan, Ruizhi Liao, William Wells, Jacob Andreas, Xin Wang, Seth Berkowitz et al.
      Pages 529-539

    3. Domain-Specific Loss Design for Unsupervised Physical Training: A New Approach to Modeling Medical ML Solutions

      • Hendrik Burwinkel, Holger Matz, Stefan Saur, Christoph Hauger, Ayşe Mine Evren, Nino Hirnschall et al.
      Pages 540-550

    4. Multiatlas Calibration of Biophysical Brain Tumor Growth Models with Mass Effect

      • Shashank Subramanian, Klaudius Scheufele, Naveen Himthani, George Biros
      Pages 551-560

    5. Chest X-Ray Report Generation Through Fine-Grained Label Learning

      • Tanveer Syeda-Mahmood, Ken C. L. Wong, Yaniv Gur, Joy T. Wu, Ashutosh Jadhav, Satyananda Kashyap et al.
      Pages 561-571
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Other volumes

  1. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

  2. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

  3. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

  4. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

  5. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

  6. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

  7. Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

  8. Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data

Keywords

About this book

The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic.

The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: machine learning methodologies

Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks

Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis

Part IV: segmentation; shape models and landmark detection

Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology

Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging

Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography

Editors and Affiliations

  • University of Toronto, Toronto, Canada

    Anne L. Martel

  • The University of British Columbia, Vancouver, Canada

    Purang Abolmaesumi

  • University College London, London, UK

    Danail Stoyanov

  • École Centrale de Nantes, Nantes, France

    Diana Mateus

  • EURECOM, Biot, France

    Maria A. Zuluaga

  • Chinese Academy of Sciences, Beijing, China

    S. Kevin Zhou

  • Sorbonne University, Paris, France

    Daniel Racoceanu

  • The Hebrew University of Jerusalem, Jerusalem, Israel

    Leo Joskowicz

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