Connectomics in NeuroImaging

Name: Connectomics in NeuroImaging | First International Workshop, CNI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings
Brand: Springer
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First International Workshop, CNI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, 2017, Proceedings

Guorong Wu Paul Laurienti Leonardo Bonilha Brent C. Munsell(Editor)

Springer (Publisher)

Published on 3. September 2017

VIII, 171 pages

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978-3-319-67159-8 (ISBN)

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Content

Intro
Preface
Organization
Contents
Connectome of Autistic Brains, Global Versus Local Characterization
1 Introduction
1.1 Connectomes and Autism Spectrum Disorder
1.2 Global Metrics
1.3 Local Connectivity Differences
2 Methods
3 Data and Experimental Settings
3.1 Pre-processing and Connectome Construction
3.2 Experimental Settings
4 Results and Discussions
5 Conclusion
References
Constructing Multi-frequency High-Order Functional Connectivity Network for Diagnosis of Mild Cognit ...
Abstract
1 Introduction
2 Methods
2.1 Multi-frequency High-Order FC Networks
2.2 Feature Extraction and Classification
3 Experiments
3.1 Data
3.2 Performance Evaluation
3.3 Intra-spectrum and Inter-spectrum HONs
4 Conclusion
Acknowledgements
References
Consciousness Level and Recovery Outcome Prediction Using High-Order Brain Functional Connectivity N ...
Abstract
1 Introduction
2 Materials
3 High-Order BFCN Construction
4 Experiments
5 Conclusion
Acknowledgements
References
Discriminative Log-Euclidean Kernels for Learning on Brain Networks
1 Introduction
2 Methods and Materials
2.1 Subjects
2.2 Image Data
2.3 Image Processing
2.4 Brain Network Construction
2.5 Gaussian Process Classification
2.6 The Discriminative Log-Euclidean Kernel
2.7 Impementation Details
2.8 Classification Experiments
2.9 Group Difference Experiments
3 Results and Discussion
4 Conclusions
References
Interactive Computation and Visualization of Structural Connectomes in Real-Time
1 Introduction
2 Methods
2.1 Structural Connectivity
3 Visualization
4 Results
5 Discussion
6 Conclusion
References
Pairing-based Ensemble Classifier Learning using Convolutional Brain Multiplexes and Multi-view Brain Networks for Early Dementia Diagnosis
1 Introduction
2 Ensemble Classifier Using Paired CCA-Mapped Convolutional Brain Mutliplexes for eMCI/NC Classification
3 Results and Discussion
4 Conclusion
References
High-order Connectomic Manifold Learning for Autistic Brain State Identification
1 Introduction
2 High-Order Connectomic Manifold Learning for Unsupervised Clustering of Autistic and Healthy Brains
3 Results and Discussion
4 Conclusion
References
A Unified Bayesian Approach to Extract Network-Based Functional Differences from a Heterogeneous Patient Cohort
1 Introduction
2 Generative Model of Abnormal Communities
3 Population Study of Autism
4 Conclusion
References
FCNet: A Convolutional Neural Network for Calculating Functional Connectivity from Functional MRI
1 Introduction
2 Method
2.1 Data and Preprocessing
2.2 Functional Connectivity Through FCNet
2.3 Feature Selection and Classification
3 Experiments and Results
4 Conclusion
References
Identifying Subnetwork Fingerprints in Structural Connectomes: A Data-Driven Approach
Abstract
1 Introduction
2 Materials and Methods
2.1 Participants, MRI Acquisition, and Connectome Reconstruction
2.2 Subnetwork Feature
2.3 Person Identification Model and Performance Evaluation
2.4 Feature Selection and Majority Vote Subnetwork Feature
3 Results
4 Discussion
5 Conclusion
Acknowledgement
References
A Simple and Efficient Cylinder Imposter Approach to Visualize DTI Fiber Tracts
Abstract
1 Introduction
2 Proposed Method
2.1 Cylinder Imposter
2.2 End Imposter
3 Experiments
4 Limitations
5 Conclusion
6 Implementation
References
Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference
1 Introduction
2 Technical Background
2.1 Structural Covariance Network
2.2 Graph Filtration
2.3 Statistical Inference
3 Methods
3.1 Data Preprocessing
3.2 Structural Covariance Networks and Statistical Inference
4 Results
5 Conclusion and Discussion
References
"Evaluating Acquisition Time of rfMRI in the Human Connectome Project for Early Psychosis. How Much ...
Abstract
1 Introduction
2 Methods
2.1 Participants
2.2 Data Acquisition
2.3 Data Preprocessing
2.4 Statistical Analysis
3 Results
3.1 Correlation Matrix Reliability
3.2 Network Rank Reliability
4 Discussion and Conclusion
Acknowledgments
References
Early Brain Functional Segregation and Integration Predict Later Cognitive Performance
Abstract
1 Introduction
2 Methods and Results
2.1 An Early Developing Triple Network Model
2.2 Individual Prediction of Later Cognitive Performance
3 Discussion and Conclusions
4 Future Works and Clinical Implications
References
Measuring Brain Connectivity via Shape Analysis of fMRI Time Courses and Spectra
1 Introduction
2 FMRI Shape Analysis of Time Courses and Spectra
2.1 Elastic Functional Data Analysis of fMRI Signals Using SRVFs
2.2 fMRI Alignment and Registration:
3 Results
3.1 Visualization of Elastic Functional Alignment
3.2 Measuring Brain Connectivity After Elastic fMRI Alignment
4 Discussion
References
Topological Network Analysis of Electroencephalographic Power Maps
1 Introduction
2 Methods
3 Simulations
4 Real Data Application
5 Discussion
References
Region-Wise Stochastic Pattern Modeling for Autism Spectrum Disorder Identification and Temporal Dynamics Analysis
1 Introduction
2 Materials and Image Processing
3 ROI-Wise Temporal Dynamics Estimation
3.1 ROI-Wise HMMs Modeling
3.2 Feature Extraction and Classifier Learning
3.3 Measuring Temporal Dynamics
4 Experimental Settings and Results
4.1 Choosing Optimal Number of States in HMMs
4.2 Performance Comparison
4.3 Regional Importance and Temporal Dynamics Analysis
5 Conclusion
References
A Whole-Brain Reconstruction Approach for FOD Modeling from Multi-Shell Diffusion MRI
1 Introduction
2 Method
2.1 Voxel-Wise FOD Modeling from Multi-Shell Imaging
2.2 Whole-Brain FOD Modeling with Spatial Regularity
2.3 Spatial Regularization via Hyper-spherical Smoothing
3 Experiments
3.1 Simulation
3.2 HCP Data for Locus Coeruleus Bundle Reconstruction
4 Discussion and Conclusion
References
Topological Distances Between Brain Networks
1 Introduction
2 Matrix Norms
3 Gromov-Hausdorff Distance
4 Kolmogorov-Smirnov Distance
5 Comparisons
6 Application
7 Discussion
References
Author Index

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Connectomics in NeuroImaging

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