Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks

Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks

Non-contrast computed tomography (NCCT) is commonly used for volumetric follow-up assessment of ischemic strokes. However, manual lesion segmentation is time-consuming and subject to high inter-observer variability. The aim of this study was to develop and establish a baseline convolutional neural n...

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Bibliographic Details
Main Authors: Anup Tuladhar, Serena Schimert, Deepthi Rajashekar, Helge C. Kniep, Jens Fiehler, Nils D. Forkert
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Artificial neural networks
brain
computed tomography
computer-assisted image analysis
convolutional neural networks
deep learning
Online Access:https://ieeexplore.ieee.org/document/9096283/

Internet

https://ieeexplore.ieee.org/document/9096283/

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