Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics

Name: Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics | First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings
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First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings

M. Jorge Cardoso Tal Arbel Enzo Ferrante Xavier Pennec Adrian V. Dalca Sarah Parisot Sarang Joshi Nematollah K. Batmanghelich Aristeidis Sotiras Mads Nielsen Mert R. Sabuncu Tom Fletcher Li Shen Stanley Durrleman Stefan Sommer(Editor)

Springer (Publisher)

Published on 6. September 2017

XV, 250 pages

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978-3-319-67675-3 (ISBN)

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Content

Intro
Workshop Editors
Preface GRAIL 2017
Organization
Preface MFCA 2017
Organization
Preface MICGen 2017
Organization
Contents
First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017
Classifying Phenotypes Based on the Community Structure of Human Brain Networks
1 Introduction
2 Similarity of Brain Network Community Structures
2.1 Detecting Communities in Structural Brain Networks
2.2 Measuring Distance Between Community Structures
3 Classifying Connectomes Based on their Community Structure
4 Experiments: Network-Based Alzheimer's Disease Classification
4.1 Data and Network Construction
4.2 Experimental Setup
4.3 Results and Discussion
5 Conclusions
References
Autism Spectrum Disorder Diagnosis Using Sparse Graph Embedding of Morphological Brain Networks
1 Introduction
2 Proposed Sparse Graph Embedding of High-Order Morphological Brain Networks for Autism Classification
3 Results and Discussion
4 Conclusion
References
Topology of Surface Displacement Shape Feature in Subcortical Structures
1 Introduction
2 Methods
2.1 Shape Feature
2.2 Shape Topology
2.3 Persistent Homology
2.4 Experiments
2.5 Imaging and Demographics
3 Results
4 Discussion and Conclusion
References
Graph Geodesics to Find Progressively Similar Skin Lesion Images
1 Introduction
2 Methods
3 Results
4 Conclusions
References
Uncertainty Estimation in Vascular Networks
1 Introduction
2 Background
3 Uncertainty Estimation by Means of Sampling
3.1 Perturbation Sampler
3.2 Gibbs Sampler
4 Experiments and Results
5 Conclusion
References
Extraction of Airways with Probabilistic State-Space Models and Bayesian Smoothing
1 Introduction
2 Method
2.1 Tracking Individual Branches
2.2 Process and Measurement Models
2.3 Bayesian Smoothing
2.4 Tree as a Collection of Branches
2.5 Application to Airways
3 Experiments and Results
3.1 Data
3.2 Error Measure, Initial Parameters and Tuning
3.3 Results
4 Discussion and Conclusions
References
Detection and Localization of Landmarks in the Lower Extremities Using an Automatically Learned Conditional Random Field
1 Introduction
2 Related Work
3 Methods
3.1 Landmark Localization Using Regression Tree Ensembles
3.2 CRF with Pool of Potential Functions and ``Missing'' Label
3.3 Learning of Parameters and Removing Potentials
4 Results
5 Discussion and Conclusions
References
6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017
Bridge Simulation and Metric Estimation on Landmark Manifolds
1 Introduction
2 Landmarks Manifolds and Stochastic Landmark Dynamics
2.1 Brownian Motion
2.2 Large Deformation Stochastics
3 Brownian Bridge Simulation
3.1 Bridge Sampling
3.2 Landmark Bridge Simulation
4 Inference Algorithm
5 Numerical Experiments
5.1 Left Cardiac Ventricles
6 Conclusion
References
White Matter Fiber Segmentation Using Functional Varifolds
1 Introduction
2 White Matter Fiber Segmentation Using Functional Varifolds
2.1 Modeling Fibers Using Functional Varifolds
2.2 Fiber Clustering Using Dictionary Learning and Sparse Coding
3 Experiments
4 Conclusion
References
Prediction of the Progression of Subcortical Brain Structures in Alzheimer's Disease from Baseline
1 Introduction
2 Method
2.1 Geodesic Regression
2.2 Two Methods to Transport Spatiotemporal Trajectories of Shapes
2.3 Cognitive Scores Dynamics
3 Results
3.1 Data, Preprocessing, Parameters and Performance Metric
3.2 Geodesic Regression Extrapolation
3.3 Non Reparametrized Transport
3.4 Refining with Cognitive Dynamical Parameters
4 Conclusion
References
A New Metric for Statistical Analysis of Rigid Transformations: Application to the Rib Cage
1 Introduction
2 Defining an Adapted Metric for Elongated Structures
2.1 Limits of the Current Metric
2.2 A New Metric for Elongated Objects
3 Statistical Description of Rigid Transformations
3.1 Pose Variations
3.2 Generalized Covariance
3.3 Application to the Rib Cage
4 Conclusion
References
Unbiased Diffeomorphic Mapping of Longitudinal Data with Simultaneous Subject Specific Template Estimation
1 Introduction
2 Methods
2.1 Diffeomorphisms and Geodesics
2.2 Sparse Parameterization
2.3 Group Actions and Notation
2.4 Cost Function for Timeseries Mapping
2.5 Optimization Algorithm
2.6 Atrophy in the Medial Temporal Lobe
3 Results
3.1 Template Estimation and Longitudinal Mapping
3.2 Processing Bias
4 Conclusion
References
Exact Function Alignment Under Elastic Riemannian Metric
1 Introduction
2 Mathematical Background
3 Pairwise Alignment Theory
4 The Matching Algorithm
4.1 The Contribution of an Up- or Down-Segment
4.2 The Matching Graph
4.3 Finding Optimal Matching
5 Multiple Function Alignment
6 Experimental Results
7 Conclusion
References
Varifold-Based Matching of Curves via Sobolev-Type Riemannian Metrics
1 Introduction
2 Mathematical Background
2.1 Sobolev Metrics on Shape Space of Curves
2.2 Varifold Distance on the Space of Curves
2.3 Inexact Matching on the Shape Space of Curves
3 Implementation
4 Experiments
5 Conclusions
References
Computational Anatomy in Theano
1 Introduction
1.1 Background
2 Geodesics
3 Christoffel Symbols
4 Fréchet Mean
5 Normal Distributions and Stochastic Development
6 Fréchet Mean on Frame Bundle
7 Conclusion
References
Rank Constrained Diffeomorphic Density Motion Estimation for Respiratory Correlated Computed Tomography
1 Introduction
2 Low Rank Motion Estimation
3 Singular Value Thresholding and Implementation
4 Application to Respiratory 4DCT Phase Registration
5 Discussion
References
Efficient Parallel Transport in the Group of Diffeomorphisms via Reduction to the Lie Algebra
1 Introduction
2 Background on Diffeomorphisms and LDDMM
2.1 Diffeomorphisms
2.2 LDDMM Image Registration
2.3 Decoupling Diffeomorphisms from Images
3 Parallel Transport
3.1 Parallel Transport Equation
3.2 Computational Complexity Analysis
3.3 Implementation Details
4 Experiments
4.1 Synthetic Data
4.2 Real Data
5 Conclusion
References
Third International Workshop on Imaging Genetics, MICGen 2017
Multi-modal Image Classification Using Low-Dimensional Texture Features for Genomic Brain Tumor Recognition
1 Introduction
2 Methods
2.1 Bag-of-Patterns: From Local Image Features to Image Region Descriptors
2.2 Unsupervised Feature Learning Based on Deep Auto-Encoders
3 Experiments
4 Conclusion
References
A Fast SCCA Algorithm for Big Data Analysis in Brain Imaging Genetics
1 Introduction
2 The Fast SCCA Algorithm
3 Experiments
3.1 Results on Synthetic Data
3.2 Results on Real Neuroimaging Genetics Data
4 Conclusions
References
Transcriptome-Guided Imaging Genetic Analysis via a Novel Sparse CCA Algorithm
1 Introduction
2 Problem Formulation
3 Methods
3.1 Update of u with v fixed
3.2 Update of v with u fixed
4 Experimental Results and Discussions
4.1 Selection of Tuning Parameters , c1 and c2
4.2 Results
5 Conclusions
References
Multilevel Modeling with Structured Penalties for Classification from Imaging Genetics Data
1 Introduction
2 Model Set-up
2.1 Multilevel Logistic Regression with Structured Penalties
2.2 Minimization of , I, I, 0)
3 Experimental Results
3.1 Dataset
3.2 Results
4 Conclusion
A Probabilistic Formulation
References
Coupled Dimensionality-Reduction Model for Imaging Genomics
1 Introduction
2 SCyLIG Model for Imaging Genomics
2.1 Dictionary Learning Methods
2.2 SCyLIG Formulation
2.3 SCyLIG Optimization
3 Experiments
4 Conclusion
References
Author Index

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Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics

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