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A deep transfer learning model for early prediction of cognitive deficits using brain structural connectome data in very preterm infants

A Deep Transfer Learning Model to Predict Patient Outcome in ICH using the Fusion of Clinical and Fluid-Attenuated Inversion Recovery Imaging Data

Disrupted grey matter network morphology in amyotrophic lateral sclerosis

Early prediction of neurodevelopmental deficits in very preterm infants using a multi-task deep transfer learning model

Improving tumor-tissue contrast by increasing spatial resolution

A machine learning model using T2-weighted FLAIR radiomics features to predict patient outcome in ICH

Simple Method for Off-Resonance Gas Artifact Removal in 129Xe Gas-Transfer MRI

Author:Matthew Willmering  Peter Niedbalski  Laura Walkup  Zackary Cleveland  Jason Woods  

Institution:Cincinnati Children's Hospital Medical Center  University of Cincinnati  

Session Type:Digital Poster  

Session Live Q&A Date:Digital Poster (All Week)  

Topic:Thoracic and Breast MRI  

Session Name:Hyperpolarized Gas Lung MRI  

Program Number:2282  

Room Live Q&A Session:

Topologically Convergent and Divergent Morphological Grey Matter Networks in Parkinson’s Disease with and without Mild Cognitive Impairment

Virtual bronchoscopy of neonatal dynamic airway collapse with ultrashort echo-time MRI