Chinese Journal of Stroke ›› 2021, Vol. 16 ›› Issue (07): 651-656.DOI: 10.3969/j.issn.1673-5765.2021.07.003
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Received:
2021-05-06
Online:
2021-07-20
Published:
2021-07-20
吴韵阳, 高键东, 吴及
通讯作者:
吴及 wuji_ee@tsinghua.edu.cn
基金资助:
WU Yun-Yang, GAO Jian-Dong, WU Ji. Application of Artificial Intelligence Imaging in Diagnosis and Treatment of Stroke[J]. Chinese Journal of Stroke, 2021, 16(07): 651-656.
吴韵阳, 高键东, 吴及. 人工智能影像技术在卒中诊疗中的应用[J]. 中国卒中杂志, 2021, 16(07): 651-656.
[1] WANG W Z,JIANG B,SUN H X,et al. Prevalence, incidence,and mortality of stroke in China:results from a nationwide population-based survey of 480 687 adults[J]. Circulation,2017,135(8):759-771. [2] 王拥军,李子孝,丁玲玲. 人工智能在卒中诊疗的研 究和应用:曙光初现,任重道远[J]. 中国卒中杂志, 2020,15(3):223-227. [3] 彭斌,吴波. 中国急性缺血性卒中诊治指南2018[J]. 中华神经科杂志,2018,51(9):666-682. [4] TANG F H,NG D K,CHOW D K. An image feature approach for computer-aided detection of ischemic stroke[J]. Comput Biol Med,2011,41(7): 529-536. [5] ABEDI V,GOYAL N,TSIVGOULIS G,et al. Novel screening tool for stroke using artificial neural network[J]. Stroke,2017,48(6):1678-1681. [6] CHEN L,BENTLEY P,RUECKERT D. Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks[J/OL]. Neuroimage Clin,2017,15:633-643[2021-05-01]. https://doi.org/10.1016/j.nicl.2017.06.016. [7] GUERRERO R,QIN C,OKTAY O,et al. White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks[J/OL]. Neuroimage Clin,2018,17:918- 934[2021-05-01]. https://doi.org/10.1016/j.nicl.2017. 12.022. [8] ÖMAN O,MÄKELÄ T,SALLI E,et al. 3D convolutional neural networks applied to CT angiography in the detection of acute ischemic stroke[J]. Eur Radiol Exp,2019,3(1):1-11. [9] TAKAHASHI N,LEE Y,TSAI D,et al. An automated detection method for the MCA dot sign of acute stroke in unenhanced CT[J]. Radiol Phys Technol,2014,7(1):79-88. [10] CHEN Z C,ZHANG R T,XU F Z,et al. Novel prehospital prediction model of large vessel occlusion using artificial neural network[J/OL]. Front Aging Neurosci,2018,10:181[2021-05-01]. https://doi.org/10.3389/fnagi.2018.00181. [11] MURRAY N M,UNBERATH M,HAGER G D,et al. Artificial intelligence to diagnose ischemic stroke and identify large vessel occlusions:a systematic review[J]. J Neurointerv Surg,2020,12(2):156- 164. [12] CHATTERJEE A,SOMAYAJI N R,KABAKIS I M. Abstract WMP16:artificial intelligence detection of cerebrovascular large vessel occlusion-nine month, 650 patient evaluation of the diagnostic accuracy and performance of the Viz. ai LVO algorithm[J/OL]. Stroke,2019,50(Suppl_1):AWMP16[2021-05-01]. https://doi.org/10.1161/str.50.suppl_1.WMP16. [13] BARREIRA C,BOUSLAMA M,LIM J,et al. E-108 Aladin study:automated large artery occlusion detection in stroke imaging study–a multicenter analysis[J/OL]. J Neurointerv Surg,2018, 10(Suppl 2):A101-A102[2021-05-01]. https://doi. org/10.1136/neurintsurg-2018-SNIS.184. [14] GOYAL M,DEMCHUK A M,MENON B K,et al. Randomized assessment of rapid endovascular treatment of ischemic stroke[J]. N Engl J Med,2015, 372(11):1019-1030. [15] NAGEL S,SINHA D,DAY D,et al. e-ASPECTS software is non-inferior to neuroradiologists in applying the ASPECT score to computed tomography scans of acute ischemic stroke patients[J]. Int J Stroke,2017,12(6):615-622. [16] GUBERINA N,DIETRICH U,RADBRUCH A,et al. Detection of early infarction signs with machine learning-based diagnosis by means of the Alberta Stroke Program Early CT Score(ASPECTS)in the clinical routine[J]. Neuroradiology,2018,60(9): 889-901. [17] KUANG H,NAJM M,CHAKRABORTY D,et al. Automated ASPECTS on noncontrast CT scans in patients with acute ischemic stroke using machine learning[J]. AJNR Am J Neuroradiol,2019,40(1): 33-38. [18] GRUNWALD I Q,KULIKOVSKI J,REITH W,et al. Collateral automation for triage in stroke:
evaluating automated scoring of collaterals in |
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