Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

Table of Contents

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   Book Overview
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   Chapter 1 Multimodal Fusion of Brain Networks with Longitudinal Couplings
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   Chapter 2 Penalized Geodesic Tractography for Mitigating Gyral Bias
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   Chapter 3 Anchor-Constrained Plausibility (ACP): A Novel Concept for Assessing Tractography and Reducing False-Positives
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   Chapter 4 Tract-Specific Group Analysis in Fetal Cohorts Using in utero Diffusion Tensor Imaging
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   Chapter 5 Tract Orientation Mapping for Bundle-Specific Tractography
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   Chapter 6 A Multi-Tissue Global Estimation Framework for Asymmetric Fiber Orientation Distributions
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   Chapter 7 Better Fiber ODFs from Suboptimal Data with Autoencoder Based Regularization
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   Chapter 8 Identification of Gadolinium Contrast Enhanced Regions in MS Lesions Using Brain Tissue Microstructure Information Obtained from Diffusion and T2 Relaxometry MRI
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    Chapter 9 A Bayes Hilbert Space for Compartment Model Computing in Diffusion MRI
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    Chapter 10 Detection and Delineation of Acute Cerebral Infarct on DWI Using Weakly Supervised Machine Learning
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    Chapter 11 Identification of Species-Preserved Cortical Landmarks
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    Chapter 12 Deep Learning with Synthetic Diffusion MRI Data for Free-Water Elimination in Glioblastoma Cases
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    Chapter 13 Enhancing Clinical MRI Perfusion Maps with Data-Driven Maps of Complementary Nature for Lesion Outcome Prediction
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    Chapter 14 Harmonizing Diffusion MRI Data Across Magnetic Field Strengths
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    Chapter 15 Normative Modeling of Neuroimaging Data Using Scalable Multi-task Gaussian Processes
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    Chapter 16 Multi-layer Large-Scale Functional Connectome Reveals Infant Brain Developmental Patterns
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    Chapter 17 A Riemannian Framework for Longitudinal Analysis of Resting-State Functional Connectivity
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    Chapter 18 Elastic Registration of Single Subject Task Based fMRI Signals
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    Chapter 19 A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data
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    Chapter 20 3D Deep Convolutional Neural Network Revealed the Value of Brain Network Overlap in Differentiating Autism Spectrum Disorder from Healthy Controls
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    Chapter 21 Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)
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    Chapter 22 The Dynamic Measurements of Regional Brain Activity for Resting-State fMRI: d-ALFF, d-fALFF and d-ReHo
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    Chapter 23 rfDemons: Resting fMRI-Based Cortical Surface Registration Using the BrainSync Transform
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    Chapter 24 Brain Biomarker Interpretation in ASD Using Deep Learning and fMRI
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    Chapter 25 Neural Activation Estimation in Brain Networks During Task and Rest Using BOLD-fMRI
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    Chapter 26 Identification of Multi-scale Hierarchical Brain Functional Networks Using Deep Matrix Factorization
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    Chapter 27 Identification of Temporal Transition of Functional States Using Recurrent Neural Networks from Functional MRI
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    Chapter 28 Identifying Personalized Autism Related Impairments Using Resting Functional MRI and ADOS Reports
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    Chapter 29 Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis
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    Chapter 30 Structured Deep Generative Model of fMRI Signals for Mental Disorder Diagnosis
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    Chapter 31 Cardiac Cycle Estimation for BOLD-fMRI
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    Chapter 32 Probabilistic Source Separation on Resting-State fMRI and Its Use for Early MCI Identification
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    Chapter 33 Identifying Brain Networks of Multiple Time Scales via Deep Recurrent Neural Network
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    Chapter 34 A Novel Deep Learning Framework on Brain Functional Networks for Early MCI Diagnosis
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    Chapter 35 A Region-of-Interest-Reweight 3D Convolutional Neural Network for the Analytics of Brain Information Processing
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    Chapter 36 Quantitative Deconvolution of fMRI Data with Multi-echo Sparse Paradigm Free Mapping
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    Chapter 37 Brain Decoding from Functional MRI Using Long Short-Term Memory Recurrent Neural Networks
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    Chapter 38 Learning Generalizable Recurrent Neural Networks from Small Task-fMRI Datasets
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    Chapter 39 Fast Mapping of the Eloquent Cortex by Learning L2 Penalties
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    Chapter 40 Combining Multiple Connectomes via Canonical Correlation Analysis Improves Predictive Models
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    Chapter 41 Exploring Fiber Skeletons via Joint Representation of Functional Networks and Structural Connectivity
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    Chapter 42 Phase Angle Spatial Embedding (PhASE)
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    Chapter 43 Edema-Informed Anatomically Constrained Particle Filter Tractography
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    Chapter 44 Thalamic Nuclei Segmentation Using Tractography, Population-Specific Priors and Local Fibre Orientation
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    Chapter 45 On Quantifying Local Geometric Structures of Fiber Tracts
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    Chapter 46 Modeling Longitudinal Voxelwise Feature Change in Normal Aging with Spatial-Anatomical Regularization
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    Chapter 47 Volume-Based Analysis of 6-Month-Old Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis
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    Chapter 48 A Tetrahedron-Based Heat Flux Signature for Cortical Thickness Morphometry Analysis
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    Chapter 49 Graph of Brain Structures Grading for Early Detection of Alzheimer’s Disease
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    Chapter 50 Joint Prediction and Classification of Brain Image Evolution Trajectories from Baseline Brain Image with Application to Early Dementia
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    Chapter 51 Temporal Correlation Structure Learning for MCI Conversion Prediction
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    Chapter 52 Synthesizing Missing PET from MRI with Cycle-consistent Generative Adversarial Networks for Alzheimer’s Disease Diagnosis
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    Chapter 53 Exploratory Population Analysis with Unbalanced Optimal Transport
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    Chapter 54 Multi-modal Synthesis of ASL-MRI Features with KPLS Regression on Heterogeneous Data
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    Chapter 55 A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models
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    Chapter 56 Deep Convolutional Networks for Automated Detection of Epileptogenic Brain Malformations
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    Chapter 57 Binary Glioma Grading: Radiomics versus Pre-trained CNN Features
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    Chapter 58 Automatic Irregular Texture Detection in Brain MRI Without Human Supervision
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    Chapter 59 Learning Myelin Content in Multiple Sclerosis from Multimodal MRI Through Adversarial Training
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    Chapter 60 Deep Multi-structural Shape Analysis: Application to Neuroanatomy
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    Chapter 61 Computational Modelling of Pathogenic Protein Behaviour-Governing Mechanisms in the Brain
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    Chapter 62 Generative Discriminative Models for Multivariate Inference and Statistical Mapping in Medical Imaging
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    Chapter 63 Using the Anisotropic Laplace Equation to Compute Cortical Thickness
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    Chapter 64 Dilatation of Lateral Ventricles with Brain Volumes in Infants with 3D Transfontanelle US
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    Chapter 65 Do Baby Brain Cortices that Look Alike at Birth Grow Alike During the First Year of Postnatal Development?
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    Chapter 66 Multi-label Transduction for Identifying Disease Comorbidity Patterns
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    Chapter 67 Text to Brain: Predicting the Spatial Distribution of Neuroimaging Observations from Text Reports
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    Chapter 68 Semi-supervised Learning for Segmentation Under Semantic Constraint
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    Chapter 69 Autofocus Layer for Semantic Segmentation
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    Chapter 70 3D Segmentation with Exponential Logarithmic Loss for Highly Unbalanced Object Sizes
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    Chapter 71 Revealing Regional Associations of Cortical Folding Alterations with In Utero Ventricular Dilation Using Joint Spectral Embedding
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    Chapter 72 CompNet: Complementary Segmentation Network for Brain MRI Extraction
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    Chapter 73 One-Pass Multi-task Convolutional Neural Networks for Efficient Brain Tumor Segmentation
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    Chapter 74 Deep Recurrent Level Set for Segmenting Brain Tumors
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    Chapter 75 Pulse Sequence Resilient Fast Brain Segmentation
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    Chapter 76 Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks
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    Chapter 77 Registration-Free Infant Cortical Surface Parcellation Using Deep Convolutional Neural Networks
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    Chapter 78 Joint Segmentation of Intracerebral Hemorrhage and Infarct from Non-Contrast CT Images of Post-treatment Acute Ischemic Stroke Patients
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    Chapter 79 Patch-Based Mapping of Transentorhinal Cortex with a Distributed Atlas
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    Chapter 80 Spatially Localized Atlas Network Tiles Enables 3D Whole Brain Segmentation from Limited Data
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    Chapter 81 Adaptive Feature Recombination and Recalibration for Semantic Segmentation: Application to Brain Tumor Segmentation in MRI
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    Chapter 82 Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection