Connectivity implicated in AD and MCI
Interpretable Feature Learning Using Multi-Output Takagi-Sugeno-Kang Fuzzy System for Multi-center ASD Diagnosis
Interpretable Multimodality Embedding Of Cerebral Cortex Using Attention Graph Network For Identifying Bipolar Disorder
Miscellaneous Neuroimaging
Doubly Weak Supervision of Deep Learning Models for Head CT
Detecting Acute Strokes from Non-Contrast CT Scan Data Using Deep Convolutional Neural Networks
FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images
Regression-based Line Detection Network for Delineation of Largely Deformed Brain Midline
Siamese U-Net with Healthy Template for Accurate Segmentation of Intracranial Hemorrhage
Automated Infarct Segmentation from Follow-up Non-Contrast CT Scans in Patients with Acute Ischemic Stroke Using Dense Multi-Path Contextual Generative Adversarial Network
Recurrent sub-volume analysis of head CT scans for the detection of intracranial hemorrhage
Cephalometric Landmark Detection by Attentive Feature Pyramid Fusion and Regression-Voting fast, consistent tractography segmentation across populations and dMRI acquisitions
Improved Placental Parameter Estimation Using Data-Driven Bayesian Modelling
Optimal experimental design for biophysical modelling in multidimensional diffusion MRI
DeepTract: A Probabilistic Deep Learning Framework for White Matter Fiber Tractography
Fast and Scalable Optimal Transport for Brain Tractograms
A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes
Constructing Consistent Longitudinal Brain Networks by Group-wise Graph Learning
Functional Neuroimaging (fMRI)
Multi-layer temporal network analysis reveals increasing temporal reachability and spreadability in the first two years of life
A matched filter decomposition of fMRI into resting and task components
Identification of Abnormal Circuit Dynamics in Major Depressive Disorder via Multiscale Neural Modeling of Resting-state fMRI
Integrating Functional and Structural Connectivities via Diffusion-Convolution-Bilinear Neural Network
Invertible Network for Classification and Biomarker Selection for ASD
Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data
Revealing Functional Connectivity by Learning Graph Laplacian
Constructing Multi-Scale Connectome Atlas by Learning Common Topology of Brain Networks
Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale
Identify Hierarchical Structures from Task-based fMRI Data via Hybrid Spatiotemporal Neural Architecture Search Net
A Deep Learning Framework for Noise Component Detection from Resting-state Functional MRI
A Novel Graph Wavelet Model for Brain Multi-Scale Functional-structural Feature Fusion
Combining Multiple Behavioral Measures and Multiple Connectomes via Multiway Canonical Correlation Analysis
Decoding brain functional.