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Artificial Intelligence and Stroke Imaging: A West Coast Perspective

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Artificial Intelligence and Stroke Imaging: A West Coast Perspective. / Zhu, Guangming; Jiang, Bin; Chen, Hui; Tong, Elizabeth; Xie, Yuan; Faizy, Tobias D; Heit, Jeremy J; Zaharchuk, Greg; Wintermark, Max.

In: NEUROIMAG CLIN N AM, Vol. 30, No. 4, 11.2020, p. 479-492.

Research output: SCORING: Contribution to journal › SCORING: Review article › Research

Harvard

Zhu, G, Jiang, B, Chen, H, Tong, E, Xie, Y, Faizy, TD, Heit, JJ, Zaharchuk, G & Wintermark, M 2020, 'Artificial Intelligence and Stroke Imaging: A West Coast Perspective', NEUROIMAG CLIN N AM, vol. 30, no. 4, pp. 479-492. https://doi.org/10.1016/j.nic.2020.07.001

APA

Zhu, G., Jiang, B., Chen, H., Tong, E., Xie, Y., Faizy, T. D., Heit, J. J., Zaharchuk, G., & Wintermark, M. (2020). Artificial Intelligence and Stroke Imaging: A West Coast Perspective. NEUROIMAG CLIN N AM, 30(4), 479-492. https://doi.org/10.1016/j.nic.2020.07.001

Vancouver

Zhu G, Jiang B, Chen H, Tong E, Xie Y, Faizy TD et al. Artificial Intelligence and Stroke Imaging: A West Coast Perspective. NEUROIMAG CLIN N AM. 2020 Nov;30(4):479-492. https://doi.org/10.1016/j.nic.2020.07.001

Bibtex

@article{ddc0a84079e84733acef9dfa943678e9,
title = "Artificial Intelligence and Stroke Imaging: A West Coast Perspective",
abstract = "Artificial intelligence (AI) advancements have significant implications for medical imaging. Stroke is the leading cause of disability and the fifth leading cause of death in the United States. AI applications for stroke imaging are a topic of intense research. AI techniques are well-suited for dealing with vast amounts of stroke imaging data and a large number of multidisciplinary approaches used in classification, risk assessment, segmentation tasks, diagnosis, prognosis, and even prediction of therapy responses. This article addresses this topic and seeks to present an overview of machine learning and/or deep learning applied to stroke imaging.",
keywords = "Artificial Intelligence, Brain/diagnostic imaging, Diagnostic Imaging/methods, Humans, Image Interpretation, Computer-Assisted/methods, Neuroimaging/methods, Stroke/diagnostic imaging, United States",
author = "Guangming Zhu and Bin Jiang and Hui Chen and Elizabeth Tong and Yuan Xie and Faizy, {Tobias D} and Heit, {Jeremy J} and Greg Zaharchuk and Max Wintermark",
note = "Copyright {\textcopyright} 2020 Elsevier Inc. All rights reserved.",
year = "2020",
month = nov,
doi = "10.1016/j.nic.2020.07.001",
language = "English",
volume = "30",
pages = "479--492",
journal = "NEUROIMAG CLIN N AM",
issn = "1052-5149",
publisher = "W.B. Saunders Ltd",
number = "4",

}

RIS

TY - JOUR

T1 - Artificial Intelligence and Stroke Imaging: A West Coast Perspective

AU - Zhu, Guangming

AU - Jiang, Bin

AU - Chen, Hui

AU - Tong, Elizabeth

AU - Xie, Yuan

AU - Faizy, Tobias D

AU - Heit, Jeremy J

AU - Zaharchuk, Greg

AU - Wintermark, Max

N1 - Copyright © 2020 Elsevier Inc. All rights reserved.

PY - 2020/11

Y1 - 2020/11

N2 - Artificial intelligence (AI) advancements have significant implications for medical imaging. Stroke is the leading cause of disability and the fifth leading cause of death in the United States. AI applications for stroke imaging are a topic of intense research. AI techniques are well-suited for dealing with vast amounts of stroke imaging data and a large number of multidisciplinary approaches used in classification, risk assessment, segmentation tasks, diagnosis, prognosis, and even prediction of therapy responses. This article addresses this topic and seeks to present an overview of machine learning and/or deep learning applied to stroke imaging.

AB - Artificial intelligence (AI) advancements have significant implications for medical imaging. Stroke is the leading cause of disability and the fifth leading cause of death in the United States. AI applications for stroke imaging are a topic of intense research. AI techniques are well-suited for dealing with vast amounts of stroke imaging data and a large number of multidisciplinary approaches used in classification, risk assessment, segmentation tasks, diagnosis, prognosis, and even prediction of therapy responses. This article addresses this topic and seeks to present an overview of machine learning and/or deep learning applied to stroke imaging.

KW - Artificial Intelligence

KW - Brain/diagnostic imaging

KW - Diagnostic Imaging/methods

KW - Humans

KW - Image Interpretation, Computer-Assisted/methods

KW - Neuroimaging/methods

KW - Stroke/diagnostic imaging

KW - United States

U2 - 10.1016/j.nic.2020.07.001

DO - 10.1016/j.nic.2020.07.001

M3 - SCORING: Review article

C2 - 33038998

VL - 30

SP - 479

EP - 492

JO - NEUROIMAG CLIN N AM

JF - NEUROIMAG CLIN N AM

SN - 1052-5149

IS - 4

ER -