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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.authorLi, Chen-Huaen_US
dc.contributor.authorWang, Jing-Yien_US
dc.contributor.authorChen, Chi-Jenen_US
dc.contributor.authorLin, Huey-Juanen_US
dc.contributor.authorSmith, Eric Edwarden_US
dc.contributor.authorWu, Hsiao-Kuangen_US
dc.contributor.authorSung, Sheng-Fengen_US
dc.contributor.authorYeh, Poh-Shiowen_US
dc.contributor.authorHsin, Yue-Loongen_US
dc.date.accessioned2014-12-08T15:36:42Z-
dc.date.available2014-12-08T15:36:42Z-
dc.date.issued2014-08-15en_US
dc.identifier.issn1932-6203en_US
dc.identifier.urihttp://dx.doi.org/10.1371/journal.pone.0104011en_US
dc.identifier.urihttp://hdl.handle.net/11536/25063-
dc.description.abstractWhite matter hyperintensities (WMHs) of presumed vascular origin are common in ageing population, especially in patients with acute cerebral infarction and the volume has been reported to be associated with mental impairment and the risk of hemorrhage from antithrombotic agents. WMHs delineation can be computerized to minimize human bias. However, the presence of cerebral infarcts greatly degrades the accuracy of WMHs detection and thus limits the application of computerized delineation to patients with acute cerebral infarction. We propose a computer-assisted segmentation method to depict WMHs in the presence of cerebral infarcts in combined T1-weighted, fluid attenuation inversion recovery, and diffusion-weighted magnetic resonance imaging (MRI). The proposed method detects WMHs by empirical threshold and atlas information, with subtraction of white matter voxels affected by acute infarction. The method was derived using MRI from 25 hemispheres with WMHs only and 13 hemispheres with both WMHs and cerebral infarcts. Similarity index (SI) and correlation were utilized to assess the agreement between the new automated method and a gold standard visually guided semi-automated method done by an expert rater. The proposed WMHs segmentation approach produced average SI, sensitivity and specificity of 83.142 +/- 11.742, 84.154 +/- 16.086 and 99.988 +/- 0.029% with WMHs only and of 68.826 +/- 14.036, 74.381 +/- 18.473 and 99.956 +/- 0.054% with both WMHs and cerebral infarcts in the derivation cohort. The performance of the proposed method with an external validation cohort was also highly consistent with that of the experienced rater.en_US
dc.language.isoen_USen_US
dc.titleAutomated Segmentation and Quantification of White Matter Hyperintensities in Acute Ischemic Stroke Patients with Cerebral Infarctionen_US
dc.typeArticleen_US
dc.identifier.doi10.1371/journal.pone.0104011en_US
dc.identifier.journalPLOS ONEen_US
dc.citation.volume9en_US
dc.citation.issue8en_US
dc.citation.epageen_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:000340879300011-
dc.citation.woscount0-
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