Improving the diagnosis of acute ischemic stroke on non-contrast CT using deep learning: a multicenter study

被引:0
作者
Weidao Chen
Jiangfen Wu
Ren Wei
Shuang Wu
Chen Xia
Dawei Wang
Daliang Liu
Longmei Zheng
Tianyu Zou
Ruijiang Li
Xianrong Qi
Xiaotong Zhang
机构
[1] Zhejiang University,Interdisciplinary Institute of Neuroscience and Technology, College of Biomedical Engineering and Instrument Science
[2] Peking University,Academy for Advanced Interdisciplinary Studies
[3] Infervision Institute of Research,Medical Imaging Center
[4] Liaocheng People’s Hospital,Department of Radiation Oncology
[5] Ankang Central Hospital,School of Pharmaceutical Sciences
[6] Weihai Municipal Hospital,Beijing Key Laboratory of Molecular Pharmaceutics and New Drug Delivery System, School of Pharmaceutical Sciences
[7] Stanford University School of Medicine,College of Electrical Engineering
[8] Peking University,MOE Frontier Science Center for Brain Science & Brain
[9] Peking University,machine Integration
[10] Zhejiang University,undefined
[11] Zhejiang University,undefined
来源
Insights into Imaging | / 13卷
关键词
Deep learning; Non-contrast computed tomography; Early ischemic changes; Alberta Stroke Program Early Computed Tomography Score; Multi-reader and multi-center study; Acute ischemic stroke;
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学科分类号
摘要
The model simultaneously segments infarcts and estimates ASPECTS by using baseline CT.A mirror-assembly module plus dual-path DCNN model improved the segmentation efficiency.We evaluated the model in a multi-reader and multicenter (MRMC) setting.
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