Automatic Assessment of DWI-ASPECTS for Assessment of Acute Ischemic Stroke using Recurrent Residual Convolutional Network

Decoupling the default mode network and global state oscillation by neural network-based prediction of the fMRI signal fluctuation

Deep-Learning based Segmentation and Localization of White Matter Hyperintensities on Magnetic Resonance Images

An end-to-end MR-based classification of arteriolar sclerosis using 3D convolutional neural networks

Fast prediction of whole-brain cerebral microbleed masks from 7T SWI imaging with a deep residual 3D UNet

Author:James Golden  Yicheng Chen  Melanie Morrison  Kate Nelson  Janine Lupo  

Institution:University of California San Francisco  

Session Type:Digital Poster  

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

Topic:Neuroimaging and AI  

Session Name:Neuroimaging & AI: Applications from Stroke to MS  

Program Number:1869  

Room Live Q&A Session:

Fetal Cortical Plate Segmentation using 2D Recurrent Residual U-Net with Plane Aggregation

Author:Jinwoo Hong  HyukJin Yun  Gilsoon Park  Jong-Min Lee  Kiho Im  

Institution:Boston Children's Hospital  Hanyang University  

Session Type:Digital Poster  

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

Topic:Neuroimaging and AI  

Session Name:Neuroimaging & AI: Applications from Stroke to MS  

Program Number:1870  

Room Live Q&A Session:

Realistic MRI simulation pipeline for anatomically variable normal young, aging and diseased brain

A robust transfer learning method to improve early diagnosis of autism spectrum disorder classification

Author:Bonian Lu  Gopikrishna Deshpande  

Institution:Auburn University  

Session Type:Digital Poster  

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

Topic:Neuroimaging and AI  

Session Name:Neuroimaging & AI: Applications from Stroke to MS  

Program Number:1872  

Room Live Q&A Session:

Transfer learning with progressive training as a novel approach for classifying clinical forms of multiple sclerosis based on clinical MRI

Using an Artificial Neural Network for Fast Mapping of the Oxygen Extraction Fraction with Combined QSM and qBOLD