Using Deep-Learning-Based Artificial Intelligence Technique to Automatically Evaluate the Collateral Status of Multiphase CTA in Acute Ischemic Stroke

Using Deep-Learning-Based Artificial Intelligence Technique to Automatically Evaluate the Collateral Status of Multiphase CTA in Acute Ischemic Stroke

Background: Collateral status is an important predictor for the outcome of acute ischemic stroke with large vessel occlusion. Multiphase computed-tomography angiography (mCTA) is useful to evaluate the collateral status, but visual evaluation of this examination is time-consuming. This study aims to...

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Bibliographic Details
Main Authors: Chun-Chao Huang, Hsin-Fan Chiang, Cheng-Chih Hsieh, Chao-Liang Chou, Zong-Yi Jhou, Ting-Yi Hou, Jin-Siang Shaw
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Tomography
Subjects:
multiphase CTA
collateral status
artificial intelligence
convolutional neural network
acute ischemic stroke
Online Access:https://www.mdpi.com/2379-139X/9/2/52

Internet

https://www.mdpi.com/2379-139X/9/2/52

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