Brain Development and Atlases
A New Metric for Characterizing Dynamic Redundancy of Dense Brain Chronnectome and Its Application to Early Detection of Alzheimer's Disease
A computational framework for dissociating development-related from individually variable flexibility in regional modularity assignment in early infancy
Domain-invariant Prior Knowledge Guided Attention Networks for Robust Skull Stripping of Developing Macaque Brains
Parkinson's Disease Detection from fMRI-derived Brainstem Regional Functional Connectivity Networks
Persistent Feature Analysis of Multimodal Brain Networks Using Generalized Fused Lasso for EMCI Identification
Recovering Brain Structural Connectivity from Functional Connectivity via Multi-GCN based Generative Adversarial Network
From Connectomic to Task-evoked Fingerprints: Individualized Prediction of Task Contrasts from Resting-state Functional Connectivity
Disentangled Intensive Triplet Autoencoder for Infant Functional Connectome Fingerprinting
COVLET: Covariance-based Wavelet-like Transform for Statistical Analysis of Brain Characteristics in Children
Species-Shared and -Specific Structural Connections Revealed by Dirty Multi-Task Regression
Self-weighted Multi-Task Learning for Subjective Cognitive Decline Diagnosis
Unified Brain Network with Functional and Structural Data
Integrating Similarity Awareness and Adaptive Calibration in Graph Convolution Network to Predict Disease
Infant Cognitive Scores Prediction With Multi-stream Attention-based Temporal Path Signature Features
Masked Multi-Task Network for Case-level Intracranial Hemorrhage Classification in Brain CT Volumes
Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates
Supervised Multi-topology Network Cross-diffusion for Population-Driven Brain Network Atlas Estimation
Partial Volume Segmentation of Brain MRI Scans of any Resolution and Contrast
BDB-Net: Boundary-enhanced Dual Branch Network for Whole Brain Segmentation
Brain Age Estimation From MRI Using a Two-Stage Cascade Network with a Ranking Loss
Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation
Optimizing Visual Cortex Parameterization with Error-Tolerant Teichmüller Map in Retinotopic Mapping
Multi-Scale Enhanced Graph Convolutional Network for Early Mild Cognitive Impairment Detection
Construction of Spatiotemporal Infant Cortical Surface Functional Templates
DWI and Tractography
Tract Dictionary Learning for Fast and Robust Recognition of Fiber Bundles
Globally Optimized Super-Resolution of Diffusion MRI Data via Fiber Continuity
White Matter Tract Segmentation with Self-supervised Learning
Estimating Tissue Microstructure with Undersampled Diffusion Data via Graph Convolutional Neural Networks
Tractogram filtering of anatomically non-plausible fibers with geometric deep learning
Unsupervised Deep Learning for Susceptibility Distortion Correction in Connectome Imaging
Hierarchical geodesic modeling on the diffusion orientation distribution function for longitudinal DW-MRI analysis
TRAKO: Efficient Transmission of Tractography Data for Visualization
Spatial Semantic-Preserving Latent Space Learning for Accelerated DWI Diagnostic Report Generation
Trajectories from Distribution-valued Functional Curves: A Unified Wasserstein Framework
Characterizing Intra-Soma Diffusion with Spherical Mean Spectrum Imaging
Functional Brain Networks
Estimating Common Harmonic Waves of Brain Networks on Stiefel Manifold
Neural Architecture Search for Optimization of Spatial-temporal Brain Network Decomposition
Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer's Disease Analysis
Enriched Representation Learning in Resting-State fMRI for Early MCI Diagnosis
Whole MILC: generalizing learned dynamics across tasks, datasets, and populations
A physics-informed geometric learning model for pathological tau spread in Alzheimer's disease
A deep pattern recognition approach for inferring respiratory volume fluctuations from fMRI data
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism
Poincare embedding reveals edge-based functional networks of the brain
The constrained network-based statistic: a new level of inference for neuroimaging
Learning Personal Representations from fMRIby Predicting Neurofeedback Performance
A 3D Convolutional Encapsulated Long Short-Term Memory (3DConv-LSTM) Model for Denoising fMRI Data
Detecting Changes of Functional Connectivity by Dynamic Graph Embedding Learning
Discovering Functional Brain Networks with 3D Residual Autoencoder (ResAE)
Spatiotemporal Attention Autoencoder (STAAE) for ADHD Classification
Global Diffeomorphic Phase Alignment of Time-series from Resting-state fMRI Data
Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis
A shared neural encoding model for the prediction of subject-specific fMRI response
Neuroimaging
Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph
Edge-variational Graph Convolutional Networks for Uncertainty-aware Disease Prediction
Fisher-Rao Regularized Transport Analysis of the Glymphatic System and Waste Drainage
Joint Neuroimage Synthesis and Representation Learning for Conversion Prediction of Subjective Cognitive Decline
Differentiable Deconvolution for Improved Stroke Perfusion Analysis
Spatial Similarity-Aware Learning and Fused Deep Polynomial Network for Detection of Obsessive-Compulsive Disorder
Deep Representation Learning For Multimodal Brain Networks
Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis
Patch-based abnormality maps for improved deep learning-based classification of Huntington's disease
A Deep Spatial Context Guided Framework for Infant Brain Subcortical Segmentation
Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE
Spatial Component Analysis to Mitigate Multiple Testing in Voxel-Based Analysis
MAGIC: Multi-scale Heterogeneity Analysis and Clustering for Brain Diseases
PIANO: Perfusion Imaging via Advection-diffusion
Hierarchical Bayesian Regression for Multi-Site Normative Modeling of Neuroimaging Data
Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks
A Disentangled Latent Space for Cross-Site MRI Harmonization
Automated Acquisition Planning for Magnetic Resonance Spectroscopy in Brain Cancer
Positron Emission Tomography
Simultaneous Denoising and Motion Estimation for Low-dose Gated PET using a Siamese Adversarial Network with Gate-to-Gate Consistency Learning
Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy
Multi-Modality Information Fusion for Radiomics-based Neural Architecture Search
Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network
Rethinking PET Image Reconstruction: Ultra-Low-Dose, Sinogram and Deep Learning
Clinically Translatable Direct Patlak Reconstruction from Dynamic PET with Motion Correction Using Convolutional Neural Network
Collimatorless Scintigraphy for Imaging Extremely Low Activity Targeted Alpha Therapy (TAT) with Weighted Robust Least Square (WRLS).