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 conferencePaper

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 languageEnglish
Publication statusPublished - Apr 2013
EventISMRM 21st Annual Meeting - Salt Lake City, United States
Duration: Apr 20 2013Apr 26 2013
https://www.ismrm.org/13/

Conference

ConferenceISMRM 21st Annual Meeting
CountryUnited States
CitySalt Lake City
Period4/20/134/26/13
Internet address

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Tsai, P-H., Chen, C-Y., Chen, C. I., Tsai, F. Y., Chung, H. W., & Chan, W. P. (2013). Segmentation-Based Quantification of Brain SWI for Predicting the Stroke Evolution. Paper presented at ISMRM 21st Annual Meeting, Salt Lake City, United States.