Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

1. Front Matter

   Pages i-xxxvii

   PDF

2. Image Reconstruction

   1. Front Matter

      Pages 1-1

      PDF

   2. Improving Amide Proton Transfer-Weighted MRI Reconstruction Using T2-Weighted Images

      • Puyang Wang, Pengfei Guo, Jianhua Lu, Jinyuan Zhou, Shanshan Jiang, Vishal M. Patel

      Pages 3-12

   3. Compressive MR Fingerprinting Reconstruction with Neural Proximal Gradient Iterations

      • Dongdong Chen, Mike E. Davies, Mohammad Golbabaee

      Pages 13-22

   4. Active MR k-space Sampling with Reinforcement Learning

      • Luis Pineda, Sumana Basu, Adriana Romero, Roberto Calandra, Michal Drozdzal

      Pages 23-33

   5. Fast Correction of Eddy-Current and Susceptibility-Induced Distortions Using Rotation-Invariant Contrasts

      • Sahar Ahmad, Ye Wu, Khoi Minh Huynh, Kim-Han Thung, Weili Lin, Dinggang Shen et al.

      Pages 34-43

   6. Joint Reconstruction and Bias Field Correction for Undersampled MR Imaging

      • Mélanie Gaillochet, Kerem Can Tezcan, Ender Konukoglu

      Pages 44-52

   7. Joint Total Variation ESTATICS for Robust Multi-parameter Mapping

      • Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner

      Pages 53-63

   8. End-to-End Variational Networks for Accelerated MRI Reconstruction

      • Anuroop Sriram, Jure Zbontar, Tullie Murrell, Aaron Defazio, C. Lawrence Zitnick, Nafissa Yakubova et al.

      Pages 64-73

   9. 3d-SMRnet: Achieving a New Quality of MPI System Matrix Recovery by Deep Learning

      • Ivo M. Baltruschat, Patryk Szwargulski, Florian Griese, Mirco Grosser, Rene Werner, Tobias Knopp

      Pages 74-82

   10. MRI Image Reconstruction via Learning Optimization Using Neural ODEs

       • Eric Z. Chen, Terrence Chen, Shanhui Sun

       Pages 83-93

   11. An Evolutionary Framework for Microstructure-Sensitive Generalized Diffusion Gradient Waveforms

       • Raphaël Truffet, Jonathan Rafael-Patino, Gabriel Girard, Marco Pizzolato, Christian Barillot, Jean-Philippe Thiran et al.

       Pages 94-103

   12. Lesion Mask-Based Simultaneous Synthesis of Anatomic and Molecular MR Images Using a GAN

       • Pengfei Guo, Puyang Wang, Jinyuan Zhou, Vishal M. Patel, Shanshan Jiang

       Pages 104-113

   13. T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitions

       • Hélène Lajous, Tom Hilbert, Christopher W. Roy, Sébastien Tourbier, Priscille de Dumast, Thomas Yu et al.

       Pages 114-124

   14. Learned Proximal Networks for Quantitative Susceptibility Mapping

       • Kuo-Wei Lai, Manisha Aggarwal, Peter van Zijl, Xu Li, Jeremias Sulam

       Pages 125-135

   15. Learning a Gradient Guidance for Spatially Isotropic MRI Super-Resolution Reconstruction

       • Yao Sui, Onur Afacan, Ali Gholipour, Simon K. Warfield

       Pages 136-146

   16. Encoding Metal Mask Projection for Metal Artifact Reduction in Computed Tomography

       • Yuanyuan Lyu, Wei-An Lin, Haofu Liao, Jingjing Lu, S. Kevin Zhou

       Pages 147-157

   17. Acceleration of High-Resolution 3D MR Fingerprinting via a Graph Convolutional Network

       • Feng Cheng, Yong Chen, Xiaopeng Zong, Weili Lin, Dinggang Shen, Pew-Thian Yap

       Pages 158-166

   18. Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness

       • Yifeng Guo, Chengjia Wang, Heye Zhang, Guang Yang

       Pages 167-177

   19. Learning MRI k-Space Subsampling Pattern Using Progressive Weight Pruning

       • Kai Xuan, Shanhui Sun, Zhong Xue, Qian Wang, Shu Liao

       Pages 178-187

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

• artificial intelligence
• bioinformatics
• color image processing
• computer aided diagnosis
• computer vision
• deep learning
• image analysis
• image matching
• image processing
• image quality
• image reconstruction
• image segmentation
• machine learning
• medical image analysis
• medical images
• neural networks
• pattern recognition
• signal processing

• 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

Policies and ethics