Segmentation-Based Quantification of Brain SWI for Predicting the Stroke Evolution

Ping-Huei Tsai; Chia-Yuen Chen; Chin I. Chen; Fong Y. Tsai; Hsiao Wen Chung; Wing P. Chan

Segmentation-Based Quantification of Brain SWI for Predicting the Stroke Evolution

Ping-Huei Tsai, Chia-Yuen Chen, Chin I. Chen, Fong Y. Tsai, Hsiao Wen Chung, Wing P. Chan

Research output: Contribution to conference › Paper › peer-review

Abstract

The aim of this study is using an auto segmentation method based on data clustering to investigate the symmetry of brain SWI in normal subjects and facilitate the quantification of the asymmetric distribution of the deoxygenated vessels in patients with acute ischemic stroke for a better prediction of the evolution. Our preliminary finding demonstrates that the proposed method provides objective information for evaluation of the patients, and may have a potential to contribute to determining the penumbra and predicting of the stroke prognosis, as well as the following treatment.

Original language	English
Publication status	Published - Apr 2013
Event	ISMRM 21st Annual Meeting - Salt Lake City, United States Duration: Apr 20 2013 → Apr 26 2013 https://www.ismrm.org/13/

Conference

Conference	ISMRM 21st Annual Meeting
Country/Territory	United States
City	Salt Lake City
Period	4/20/13 → 4/26/13
Internet address	https://www.ismrm.org/13/

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Cite this

@conference{3a6cab86b03c48d2990675c54b4f8e96,

title = "Segmentation-Based Quantification of Brain SWI for Predicting the Stroke Evolution",

abstract = "The aim of this study is using an auto segmentation method based on data clustering to investigate the symmetry of brain SWI in normal subjects and facilitate the quantification of the asymmetric distribution of the deoxygenated vessels in patients with acute ischemic stroke for a better prediction of the evolution. Our preliminary finding demonstrates that the proposed method provides objective information for evaluation of the patients, and may have a potential to contribute to determining the penumbra and predicting of the stroke prognosis, as well as the following treatment.",

author = "Ping-Huei Tsai and Chia-Yuen Chen and Chen, {Chin I.} and Tsai, {Fong Y.} and Chung, {Hsiao Wen} and Chan, {Wing P.}",

year = "2013",

month = apr,

language = "English",

note = "ISMRM 21st Annual Meeting ; Conference date: 20-04-2013 Through 26-04-2013",

url = "https://www.ismrm.org/13/",

}

TY - CONF

T1 - Segmentation-Based Quantification of Brain SWI for Predicting the Stroke Evolution

AU - Tsai, Ping-Huei

AU - Chen, Chia-Yuen

AU - Chen, Chin I.

AU - Tsai, Fong Y.

AU - Chung, Hsiao Wen

AU - Chan, Wing P.

PY - 2013/4

Y1 - 2013/4

N2 - The aim of this study is using an auto segmentation method based on data clustering to investigate the symmetry of brain SWI in normal subjects and facilitate the quantification of the asymmetric distribution of the deoxygenated vessels in patients with acute ischemic stroke for a better prediction of the evolution. Our preliminary finding demonstrates that the proposed method provides objective information for evaluation of the patients, and may have a potential to contribute to determining the penumbra and predicting of the stroke prognosis, as well as the following treatment.

AB - The aim of this study is using an auto segmentation method based on data clustering to investigate the symmetry of brain SWI in normal subjects and facilitate the quantification of the asymmetric distribution of the deoxygenated vessels in patients with acute ischemic stroke for a better prediction of the evolution. Our preliminary finding demonstrates that the proposed method provides objective information for evaluation of the patients, and may have a potential to contribute to determining the penumbra and predicting of the stroke prognosis, as well as the following treatment.

M3 - Paper

T2 - ISMRM 21st Annual Meeting

Y2 - 20 April 2013 through 26 April 2013

ER -

Segmentation-Based Quantification of Brain SWI for Predicting the Stroke Evolution

Abstract

Conference

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