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Connectomics in NeuroImaging

Second International Workshop, CNI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

  • Conference proceedings
  • © 2018
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Overview

Editors:
  1. Guorong Wu

    1. University of North Carolina at Chapel Hill, Chapel Hill, USA

  2. Islem Rekik

    1. University of Dundee, Dundee, UK

  3. Markus D. Schirmer

    1. Harvard Medical School, Boston, USA

  4. Ai Wern Chung

    1. Harvard Medical School, Boston, USA

  5. Brent Munsell

    1. College of Charleston, Charleston, USA

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11083)

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

Included in the following conference series:

Conference proceedings info: CNI 2018.

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About this book

This book constitutes the refereed proceedings of the Second International Workshop on Connectomics in NeuroImaging, CNI 2018, held in conjunction with MICCAI 2018 in Granada, Spain, in September 2018.

The 15 full papers presented were carefully reviewed and selected from 20 submissions. The papers deal with new advancements in network construction, analysis, and visualization techniques in connectomics and their use in clinical diagnosis and group comparison studies as well as in various neuroimaging applications.

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Table of contents (16 papers)

  1. Front Matter

    Pages I-X
    Download chapter PDF

  2. Towards Ultra-High Resolution 3D Reconstruction of a Whole Rat Brain from 3D-PLI Data

    • Sharib Ali, Martin Schober, Philipp Schlömer, Katrin Amunts, Markus Axer, Karl Rohr
    Pages 1-10

  3. FOD-Based Registration for Susceptibility Distortion Correction in Connectome Imaging

    • Yuchuan Qiao, Wei Sun, Yonggang Shi
    Pages 11-19

  4. GIFE: Efficient and Robust Group-Wise Isometric Fiber Embedding

    • Junyan Wang, Yonggang Shi
    Pages 20-28

  5. Multi-modal Brain Tensor Factorization: Preliminary Results with AD Patients

    • Göktekin Durusoy, Abdullah Karaaslanlı, Demet Yüksel Dal, Zerrin Yıldırım, Burak Acar
    Pages 29-37

  6. Intact Connectional Morphometricity Learning Using Multi-view Morphological Brain Networks with Application to Autism Spectrum Disorder

    • Alaa Bessadok, Islem Rekik
    Pages 38-46

  7. Neonatal Morphometric Similarity Networks Predict Atypical Brain Development Associated with Preterm Birth

    • Paola Galdi, Manuel Blesa, Gemma Sullivan, Gillian J. Lamb, David Q. Stoye, Alan J. Quigley et al.
    Pages 47-57

  8. Heritability Estimation of Reliable Connectomic Features

    • Linhui Xie, Enrico Amico, Paul Salama, Yu-chien Wu, Shiaofen Fang, Olaf Sporns et al.
    Pages 58-66

  9. Topological Data Analysis of Functional MRI Connectivity in Time and Space Domains

    • Keri L. Anderson, Jeffrey S. Anderson, Sourabh Palande, Bei Wang
    Pages 67-77

  10. Riemannian Regression and Classification Models of Brain Networks Applied to Autism

    • Eleanor Wong, Jeffrey S. Anderson, Brandon A. Zielinski, P. Thomas Fletcher
    Pages 78-87

  11. Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields

    • Naresh Nandakumar, Niharika S. D’Souza, Jeff Craley, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar et al.
    Pages 88-98

  12. Data-Specific Feature Selection Method Identification for Most Reproducible Connectomic Feature Discovery Fingerprinting Brain States

    • Nicolas Georges, Islem Rekik, for the Alzheimers’s Disease Neuroimaging Initiative
    Pages 99-106

  13. Towards Effective Functional Connectome Fingerprinting

    • Kendrick Li, Gowtham Atluri
    Pages 107-116

  14. Connectivity-Driven Brain Parcellation via Consensus Clustering

    • Anvar Kurmukov, Ayagoz Musabaeva, Yulia Denisova, Daniel Moyer, Boris Gutman
    Pages 117-126

  15. GRAND: Unbiased Connectome Atlas of Brain Network by Groupwise Graph Shrinkage and Network Diffusion

    • Guorong Wu, Brent Munsell, Paul Laurienti, Moo K. Chung
    Pages 127-135

  16. Structural Subnetwork Evolution Across the Life-Span: Rich-Club, Feeder, Seeder

    • Markus D. Schirmer, Ai Wern Chung
    Pages 136-145

  17. Correction to: GRAND: Unbiased Connectome Atlas of Brain Network by Groupwise Graph Shrinkage and Network Diffusion

    • Guorong Wu, Brent Munsell, Paul Laurienti, Moo K. Chung
    Pages C1-C1

  18. Back Matter

    Pages 147-147
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Other volumes

  1. Connectomics in NeuroImaging

Editors and Affiliations

  • University of North Carolina at Chapel Hill, Chapel Hill, USA

    Guorong Wu

  • University of Dundee, Dundee, UK

    Islem Rekik

  • Harvard Medical School, Boston, USA

    Markus D. Schirmer, Ai Wern Chung

  • College of Charleston, Charleston, USA

    Brent Munsell

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