Deep Network for the Automatic Segmentation and Quantification of Intracranial Hemorrhage on CT

Deep Network for the Automatic Segmentation and Quantification of Intracranial Hemorrhage on CT

BackgroundThe ABC/2 method is usually applied to evaluate intracerebral hemorrhage (ICH) volume on computed tomography (CT), although it might be inaccurate and not applicable in estimating extradural or subdural hemorrhage (EDH, SDH) volume due to their irregular hematoma shapes. This study aimed t...

Full description

Bibliographic Details
Main Authors: Jun Xu, Rongguo Zhang, Zijian Zhou, Chunxue Wu, Qiang Gong, Huiling Zhang, Shuang Wu, Gang Wu, Yufeng Deng, Chen Xia, Jun Ma
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-01-01
Series:Frontiers in Neuroscience
Subjects:
CT
deep learning
intracranial hemorrhage
segmentation
quantification
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2020.541817/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2020.541817/full

Similar Items