Segmentation
A Bayesian Neural Net to Segment Images with Uncertainty Estimates and Good Calibration
Explicit Topological Priors for Deep-Learning Based Image Segmentation Using Persistent Homology
Semi-Supervised and Task-Driven Data Augmentation
Classification and Inference
Analyzing Brain Morphology on the Bag-of-Features Manifold
Modeling and Inference of Spatio-Temporal Protein Dynamics Across Brain Networks
Deep Learning
InceptionGCN: Receptive Field Aware Graph Convolutional Network for Disease Prediction
Adaptive Graph Convolution Pooling for Brain Surface Analysis
On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging
A Deep Neural Network for Manifold-Valued Data with Applications to Neuroimaging
Improved Disease Classification in Chest X-rays with Transferred Features from Report Generation
Reconstruction
Limited Angle Tomography Reconstruction: Synthetic Reconstruction via Unsupervised Sinogram Adaptation
Improving Generalization of Deep Networks for Inverse Reconstruction of Image Sequences
Disease Modeling
Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia
Shape
Minimizing Non-Holonomicity: Finding Sheets in Fibrous Structures
Learning Low-Dimensional Representations of Shape Data Sets with Diffeomorphic Autoencoders
Diffeomorphic Medial Modeling
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing
Registration
Local Optimal Transport for Functional Brain Template Estimation
Unsupervised Deformable Registration for Multi-Modal Images via Disentangled Representations
Learning Motion
Real-Time 2D-3D Deformable Registration with Deep Learning and Application to Lung Radiotherapy Targeting
Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces
Functional Imaging
Integrating Convolutional Neural Networks and Probabilistic Graphical Modeling for Epileptic Seizure Detection in Multichannel EEG
A Novel Sparse Overlapping Modularized Gaussian Graphical Model for Functional Connectivity Estimation
White Matter Imaging
Asymmetry Spectrum Imaging for Baby Diffusion Tractography
A Fast Fiber k-Nearest-Neighbor Algorithm with Application to Group-Wise White Matter Topography Analysis
Posters
3D Organ Shape Reconstruction from Topogram Images
A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation
A Graph Model of the Lungs with MorphologyBased Structure for Tuberculosis Type Classification
A Longitudinal Model for Tau Aggregation in Alzheimers Disease Based on Structural Connectivity
Accurate Nuclear Segmentation with Center Vector Encoding
Bayesian Longitudinal Modeling of Early Stage Parkinsons Disease Using DaTscan Images
Brain Tumor Segmentation on MRI with Missing Modalities
Contextual Fibre Growth to Generate Realistic Axonal Packing for Diffusion MRI Simulation
DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction
ECKO: Ensemble of Clustered Knockoffs for Robust Multivariate Inference on fMRI Data
FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of Diffeomorphisms
Graph Convolutional Nets for Tool Presence Detection in Surgical Videos
High-Order Oriented Cylindrical Flux for Curvilinear Structure Detection and Vessel Segmentation
Joint CS-MRI Reconstruction and Segmentation with a Unified Deep Network
Learning a Conditional Generative Model for Anatomical Shape Analysis
Manifold Exploring Data Augmentation with Geometric Transformations for Increased Performance and Robustness
Multifold Acceleration of Diffusion MRI via Deep Learning Reconstruction from Slice-Undersampled Data
Riemannian Geometry Learning for Disease Progression Modelling
Semi-Supervised Brain Lesion Segmentation with an Adapted Mean Teacher Model
Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices with Applications to Neuroimaging
Simultaneous Spatial-temporal Decomposition of Connectome-Scale Brain Networks by Deep Sparse Recurrent Auto-Encoders
Ultrasound Image Representation Learning by Modeling Sonographer Visual Attention
A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces
A Geometric Framework for Feature Mappings in Multimodal Fusion of Brain Image Data
A Hierarchical Manifold Learning Framework for High-Dimensional Neuroimaging Data
A Model for Elastic Evolution on Foliated Shapes
Analyzing Mild Cognitive Impairment Progression via Multi-view Structural Learning
New Graph-Blind Convolutional Network for Brain Connectome Data Analysis
CIA-Net: Robust Nuclei Instance Segmentation with Contour-Aware Information Aggregation
Data-Driven Model Order Reduction For Diffeomorphic Image Registration
DGR-Net: Deep Groupwise Registration of Multispectral Images
Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery
Generalizations of Ripleys K-Function with Application to Space Curves
Group Level MEG/EEG Source Imaging via Optimal Transport: Minimum Wasserstein Estimates
InSpect: INtegrated SPECTral Component Estimation and Mapping for Multi-Contrast Microstructural MRI
Joint Inference on Structural and Diffusion MRI for Sequence-Adaptive Bayesian Segmentation of Thalamic Nuclei with Probabilistic Atlases
Learning-Based Optimization of the Under-Sampling Pattern in MRI
Melanoma Recognition via Visual Attention
Nonlinear Markov Random Fields Learned via Backpropagation
Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler
SHAMANN: Shared Memory Augmented Neural Networks
Signet Ring Cell Detection With a Semi-supervised Learning Framework
Spherical U-Net on Cortical Surfaces: Methods and Applications
Variational Autoencoder with Truncated Mixture of Gaussians for Functional Connectivity Analysis.