Fully automatic identification of post-treatment infarct lesions after endovascular therapy based on non-contrast computed tomography.

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Title: Fully automatic identification of post-treatment infarct lesions after endovascular therapy based on non-contrast computed tomography.
Authors: Nie, Ximing1,2, Liu, Xiran1,2, Yang, Hao3, Shi, Feng4, Gu, Weibin5, Hou, Xinyi5, Wei, Yufei1,2, Lu, Qixuan1,2, Bai, Haiwei6, Chen, Jiaping1,2, Liu, Tianhang1,2, Yan, Hongyi1,2, Yang, Zhonghua1,2, Wen, Miao1,2, Pan, Yuesong1,2, Huang, Chao3, chao.huang@my.cityu.edu.hk, Wang, Long3,7, Liu, Liping1,2, liuliping@bjtth.org
Source: Neural Computing & Applications; Oct2023, Vol. 35 Issue 30, p22101-22114, 14p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
An: 171995060
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  Data: Fully automatic identification of post-treatment infarct lesions after endovascular therapy based on non-contrast computed tomography.
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  Data: <searchLink fieldCode="JN" term="%22Neural+Computing+%26+Applications%22">Neural Computing & Applications</searchLink>; Oct2023, Vol. 35 Issue 30, p22101-22114, 14p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=171995060
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        Value: 10.1007/s00521-022-08094-4
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              Text: Oct2023
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              Y: 2023
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