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A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT

Published Online: 2020-11-09

Authors

Arab, Ali

Chinda, Betty

Medvedev, George

Siu, William

Guo, Hui

Gu, Tao

Moreno, Sylvain

Hamarneh, Ghassan

Ester, Martin

Song, Xiaowei
Funding

Funding for this research was provided by:

Simon Fraser University Community Trust Endowment Fund

Royal Columbian Hospital Foundation (#G2016-113)

Surrey Hospitals Foundation (#G2017-001)

Tianjin Medical University General Hospital Fellowship Award

Beijing Hospital Fellowship Award
License Information

Text and Data Mining valid from 2020-11-09

Version of Record valid from 2020-11-09
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Article History

Received: 2 June 2020

Accepted: 26 October 2020

First Online: 9 November 2020

Competing interests

: The authors declare no competing interests.

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