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Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part III

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Alejandro F. Frangi

    1. University of Leeds, Leeds, UK

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  2. Julia A. Schnabel

    1. King’s College London, London, UK

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  3. Christos Davatzikos

    1. University of Pennsylvania, Philadelphia, USA

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  4. Carlos Alberola-López

    1. Universidad de Valladolid, Valladolid, Spain

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  5. Gabor Fichtinger

    1. Queen’s University, Kingston, Canada

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11072)

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 2019.

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Table of contents (82 papers)

  1. Diffusion Tensor Imaging and Functional MRI: Functional MRI

    1. A Riemannian Framework for Longitudinal Analysis of Resting-State Functional Connectivity

      • Qingyu Zhao, Dongjin Kwon, Kilian M. Pohl
      Pages 145-153

    2. Elastic Registration of Single Subject Task Based fMRI Signals

      • David S. Lee, Joana Loureiro, Katherine L. Narr, Roger P. Woods, Shantanu H. Joshi
      Pages 154-162

    3. A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data

      • Niharika Shimona D’Souza, Mary Beth Nebel, Nicholas Wymbs, Stewart Mostofsky, Archana Venkataraman
      Pages 163-171

    4. 3D Deep Convolutional Neural Network Revealed the Value of Brain Network Overlap in Differentiating Autism Spectrum Disorder from Healthy Controls

      • Yu Zhao, Fangfei Ge, Shu Zhang, Tianming Liu
      Pages 172-180

    5. Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)

      • Yu Zhao, Xiang Li, Wei Zhang, Shijie Zhao, Milad Makkie, Mo Zhang et al.
      Pages 181-189

    6. The Dynamic Measurements of Regional Brain Activity for Resting-State fMRI: d-ALFF, d-fALFF and d-ReHo

      • Chao Tang, Yuqing Wei, Jiajia Zhao, Jingxin Nie
      Pages 190-197

    7. rfDemons: Resting fMRI-Based Cortical Surface Registration Using the BrainSync Transform

      • Anand A. Joshi, Jian Li, Minqi Chong, Haleh Akrami, Richard M. Leahy
      Pages 198-205

    8. Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI

      • Xiaoxiao Li, Nicha C. Dvornek, Juntang Zhuang, Pamela Ventola, James S. Duncan
      Pages 206-214

    9. Neural Activation Estimation in Brain Networks During Task and Rest Using BOLD-fMRI

      • Michael Hütel, Andrew Melbourne, Sebastien Ourselin
      Pages 215-222

    10. Identification of Multi-scale Hierarchical Brain Functional Networks Using Deep Matrix Factorization

      • Hongming Li, Xiaofeng Zhu, Yong Fan
      Pages 223-231

    11. Identification of Temporal Transition of Functional States Using Recurrent Neural Networks from Functional MRI

      • Hongming Li, Yong Fan
      Pages 232-239

    12. Identifying Personalized Autism Related Impairments Using Resting Functional MRI and ADOS Reports

      • Omar Dekhil, Mohamed Ali, Ahmed Shalaby, Ali Mahmoud, Andy Switala, Mohammed Ghazal et al.
      Pages 240-248

    13. Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis

      • Weizheng Yan, Han Zhang, Jing Sui, Dinggang Shen
      Pages 249-257

    14. Structured Deep Generative Model of fMRI Signals for Mental Disorder Diagnosis

      • Takashi Matsubara, Tetsuo Tashiro, Kuniaki Uehara
      Pages 258-266

    15. Cardiac Cycle Estimation for BOLD-fMRI

      • Michael Hütel, Andrew Melbourne, David L. Thomas, Sebastien Ourselin
      Pages 267-274

    16. Probabilistic Source Separation on Resting-State fMRI and Its Use for Early MCI Identification

      • Eunsong Kang, Heung-Il Suk
      Pages 275-283

    17. Identifying Brain Networks of Multiple Time Scales via Deep Recurrent Neural Network

      • Yan Cui, Shijie Zhao, Han Wang, Li Xie, Yaowu Chen, Junwei Han et al.
      Pages 284-292

    18. A Novel Deep Learning Framework on Brain Functional Networks for Early MCI Diagnosis

      • Tae-Eui Kam, Han Zhang, Dinggang Shen
      Pages 293-301

    19. A Region-of-Interest-Reweight 3D Convolutional Neural Network for the Analytics of Brain Information Processing

      • Xiuyan Ni, Zhennan Yan, Tingting Wu, Jin Fan, Chao Chen
      Pages 302-310

    20. Quantitative Deconvolution of fMRI Data with Multi-echo Sparse Paradigm Free Mapping

      • César Caballero-Gaudes, Stefano Moia, Peter A. Bandettini, Javier Gonzalez-Castillo
      Pages 311-319
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Other volumes

  1. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

  2. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

  3. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

  4. Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

  5. Computational Biomechanics for Medicine

Keywords

About this book

The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018.

The 373 revised full papers presented were carefully reviewed and selected from 1068 submissions in a double-blind review process. The papers have been organized in the following topical sections:
Part I: Image Quality and Artefacts; Image Reconstruction Methods; Machine Learning in Medical Imaging; Statistical Analysis for Medical Imaging; Image Registration Methods.
Part II: Optical and Histology Applications: Optical Imaging Applications; Histology Applications; Microscopy Applications; Optical Coherence Tomography and Other Optical Imaging Applications. Cardiac, Chest and Abdominal Applications: Cardiac Imaging Applications: Colorectal, Kidney and Liver Imaging Applications; Lung Imaging Applications; Breast Imaging Applications; Other Abdominal Applications.
Part III: Diffusion Tensor Imaging and Functional MRI: Diffusion Tensor Imaging; Diffusion Weighted Imaging; Functional MRI; Human Connectome. Neuroimaging and Brain Segmentation Methods: Neuroimaging; Brain Segmentation Methods.
Part IV: Computer Assisted Intervention: Image Guided Interventions and Surgery; Surgical Planning, Simulation and Work Flow Analysis; Visualization and Augmented Reality. Image Segmentation Methods: General Image Segmentation Methods, Measures and Applications; Multi-Organ Segmentation; Abdominal Segmentation Methods; Cardiac Segmentation Methods; Chest, Lung and Spine Segmentation; Other Segmentation Applications. 

Editors and Affiliations

  • University of Leeds, Leeds, UK

    Alejandro F. Frangi

  • King’s College London, London, UK

    Julia A. Schnabel

  • University of Pennsylvania, Philadelphia, USA

    Christos Davatzikos

  • Universidad de Valladolid, Valladolid, Spain

    Carlos Alberola-López

  • Queen’s University, Kingston, Canada

    Gabor Fichtinger

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