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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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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. 

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Table of contents (82 papers)

  1. Front Matter

    Pages I-XXIX
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  2. Diffusion Tensor Imaging and Functional MRI: Diffusion Tensor Imaging

    1. Front Matter

      Pages 1-1
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    2. Multimodal Fusion of Brain Networks with Longitudinal Couplings

      • Wen Zhang, Kai Shu, Suhang Wang, Huan Liu, Yalin Wang
      Pages 3-11

    3. Penalized Geodesic Tractography for Mitigating Gyral Bias

      • Ye Wu, Yuanjing Feng, Dinggang Shen, Pew-Thian Yap
      Pages 12-19

    4. Anchor-Constrained Plausibility (ACP): A Novel Concept for Assessing Tractography and Reducing False-Positives

      • Peter F. Neher, Bram Stieltjes, Klaus H. Maier-Hein
      Pages 20-27

    5. Tract-Specific Group Analysis in Fetal Cohorts Using in utero Diffusion Tensor Imaging

      • Shadab Khan, Caitlin K. Rollins, Cynthia M. Ortinau, Onur Afacan, Simon K. Warfield, Ali Gholipour
      Pages 28-35

    6. Tract Orientation Mapping for Bundle-Specific Tractography

      • Jakob Wasserthal, Peter F. Neher, Klaus H. Maier-Hein
      Pages 36-44

    7. A Multi-Tissue Global Estimation Framework for Asymmetric Fiber Orientation Distributions

      • Ye Wu, Yuanjing Feng, Dinggang Shen, Pew-Thian Yap
      Pages 45-52

  3. Diffusion Tensor Imaging and Functional MRI: Diffusion Weighted Imaging

    1. Front Matter

      Pages 53-53
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    2. Better Fiber ODFs from Suboptimal Data with Autoencoder Based Regularization

      • Kanil Patel, Samuel Groeschel, Thomas Schultz
      Pages 55-62

    3. Identification of Gadolinium Contrast Enhanced Regions in MS Lesions Using Brain Tissue Microstructure Information Obtained from Diffusion and T2 Relaxometry MRI

      • Sudhanya Chatterjee, Olivier Commowick, Onur Afacan, Simon K. Warfield, Christian Barillot
      Pages 63-71

    4. A Bayes Hilbert Space for Compartment Model Computing in Diffusion MRI

      • Aymeric Stamm, Olivier Commowick, Alessandra Menafoglio, Simon K. Warfield
      Pages 72-80

    5. Detection and Delineation of Acute Cerebral Infarct on DWI Using Weakly Supervised Machine Learning

      • Stefano Pedemonte, Bernardo Bizzo, Stuart Pomerantz, Neil Tenenholtz, Bradley Wright, Mark Walters et al.
      Pages 81-88

    6. Identification of Species-Preserved Cortical Landmarks

      • Tuo Zhang, Xiao Li, Lin Zhao, Ying Huang, Lei Guo, Tianming Liu
      Pages 89-97

    7. Deep Learning with Synthetic Diffusion MRI Data for Free-Water Elimination in Glioblastoma Cases

      • Miguel Molina-Romero, Benedikt Wiestler, Pedro A. Gómez, Marion I. Menzel, Bjoern H. Menze
      Pages 98-106

    8. Enhancing Clinical MRI Perfusion Maps with Data-Driven Maps of Complementary Nature for Lesion Outcome Prediction

      • Adriano Pinto, Sérgio Pereira, Raphael Meier, Victor Alves, Roland Wiest, Carlos A. Silva et al.
      Pages 107-115

    9. Harmonizing Diffusion MRI Data Across Magnetic Field Strengths

      • Suheyla Cetin Karayumak, Marek Kubicki, Yogesh Rathi
      Pages 116-124

  4. Diffusion Tensor Imaging and Functional MRI: Functional MRI

    1. Front Matter

      Pages 125-125
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    2. Normative Modeling of Neuroimaging Data Using Scalable Multi-task Gaussian Processes

      • Seyed Mostafa Kia, Andre Marquand
      Pages 127-135

    3. Multi-layer Large-Scale Functional Connectome Reveals Infant Brain Developmental Patterns

      • Han Zhang, Natalie Stanley, Peter J. Mucha, Weiyan Yin, Weili Lin, Dinggang Shen
      Pages 136-144
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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

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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