Open AccessImproving Ischemic Stroke Care With MRI and Deep Learning Artificial Intelligence
Author(s) -
Yannan Yu,
Jeremy J Heit,
Greg Zaharchuk
Publication year - 2021
Publication title -
topics in magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.547
H-Index - 53
eISSN - 1536-1004
pISSN - 0899-3459
DOI - 10.1097/rmr.0000000000000290
Subject(s) - stroke (engine) , magnetic resonance imaging , deep learning , medicine , artificial intelligence , acute stroke , ischemic stroke , physical medicine and rehabilitation , intensive care medicine , computer science , radiology , ischemia , emergency department , nursing , engineering , mechanical engineering
Advanced magnetic resonance imaging has been used as selection criteria for both acute ischemic stroke treatment and secondary prevention. The use of artificial intelligence, and in particular, deep learning, to synthesize large amounts of data and to understand better how clinical and imaging data can be leveraged to improve stroke care promises a new era of stroke care. In this article, we review common deep learning model structures for stroke imaging, evaluation metrics for model performance, and studies that investigated deep learning application in acute ischemic stroke care and secondary prevention.