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dc.contributor.authorTsai, Jang-Zernen_US
dc.contributor.authorPeng, Syu-Jyunen_US
dc.contributor.authorChen, Yu-Weien_US
dc.contributor.authorWang, Kuo-Weien_US
dc.contributor.authorWu, Hsiao-Kuangen_US
dc.contributor.authorLin, Yun-Yuen_US
dc.contributor.authorLee, Ying-Yingen_US
dc.contributor.authorChen, Chi-Jenen_US
dc.contributor.authorLin, Huey-Juanen_US
dc.contributor.authorSmith, Eric Edwarden_US
dc.contributor.authorYeh, Poh-Shiowen_US
dc.contributor.authorHsin, Yue-Loongen_US
dc.date.accessioned2014-12-08T15:35:37Z-
dc.date.available2014-12-08T15:35:37Z-
dc.date.issued2014en_US
dc.identifier.issn2314-6133en_US
dc.identifier.urihttp://hdl.handle.net/11536/24050-
dc.identifier.urihttp://dx.doi.org/10.1155/2014/963032en_US
dc.description.abstractDetermination of the volumes of acute cerebral infarct in the magnetic resonance imaging harbors prognostic values. However, semiautomatic method of segmentation is time-consuming and with high interrater variability. Using diffusion weighted imaging and apparent diffusion coefficient map from patients with acute infarction in 10 days, we aimed to develop a fully automatic algorithm to measure infarct volume. It includes an unsupervised classification with fuzzy C-means clustering determination of the histographic distribution, defining self-adjusted intensity thresholds. The proposed method attained high agreement with the semiautomatic method, with similarity index 89.9 +/- 6.5%, in detecting cerebral infarct lesions from 22 acute stroke patients. We demonstrated the accuracy of the proposed computer-assisted prompt segmentation method, which appeared promising to replace the laborious, time-consuming, and operator-dependent semiautomatic segmentation.en_US
dc.language.isoen_USen_US
dc.titleAutomatic Detection and Quantification of Acute Cerebral Infarct by Fuzzy Clustering and Histographic Characterization on Diffusion Weighted MR Imaging and Apparent Diffusion Coefficient Mapen_US
dc.typeArticleen_US
dc.identifier.doi10.1155/2014/963032en_US
dc.identifier.journalBIOMED RESEARCH INTERNATIONALen_US
dc.contributor.department生醫電子轉譯研究中心zh_TW
dc.contributor.departmentBiomedical Electronics Translational Research Centeren_US
dc.identifier.wosnumberWOS:000333312500001-
dc.citation.woscount0-
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