A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis

Zhou，Longxi1; Li，Zhongxiao1; Zhou，Juexiao2; Li，Haoyang3; Chen，Yupeng4; Huang，Yuxin5; Xie，Dexuan6; Zhao，Lintao7; Fan，Ming8; Hashmi，Shahrukh9; Abdelkareem，Faisal10; Eiada，Riham10; Xiao，Xigang6; Li，Lihua8; Qiu，Zhaowen11; Gao，Xin1

2020-08

10.1109/TMI.2020.3001810

IEEE Transactions on Medical Imaging   影响因子和分区

1558-254X

COVID-19 deep learning segmentation computerized tomography

SCI ; EI

其他

20203409079465

Computer aided diagnosis ; Computerized tomography ; Learning algorithms ; Deep learning ; Nucleic acids ; Three dimensional computer graphics

Biomedical Engineering:461.1 ; Biological Materials and Tissue Engineering:461.2 ; Ergonomics and Human Factors Engineering:461.4 ; Health Care:461.7 ; Data Processing and Image Processing:723.2 ; Machine Learning:723.4.2 ; Computer Applications:723.5 ; Biochemistry:801.2 ; Organic Compounds:804.1

CLINICAL MEDICINE

IEEE

1.Computer,Electrical and Mathematical Sciences and Engineering (CEMSE) Division,Computational Bioscience Research Center (CBRC),King Abdullah University of Science and Technology (KAUST),Thuwal,Saudi Arabia
2.Department of Biology,Southern University of Science and Technology,Shenzhen,China
3.Cancer Systems Biology Center,China-Japan Union Hospital,Jilin University,Changchun,China
4.Peng Cheng Laboratory,Shenzhen,China
5.Heilongjiang Tuomeng Technology Company Ltd.,Harbin,China
6.Department of Computer Tomography,First Affiliated Hospital of Harbin Medical University,Harbin,China
7.Department of Computer Tomography,First Hospital of Harbin Medical University,Harbin,China
8.Institute of Biomedical Engineering and Instrumentation,Hangzhou Dianzi University,Hangzhou,China
9.Oncology Center,King Faisal Specialist Hospital and Research Center,Riyadh,Saudi Arabia
10.Department Medical Imaging,King Faisal Specialist Hospital and Research Center,Riyadh,Saudi Arabia
11.Institute of Information and Computer Engineering,Northeast Forestry University,Harbin,China

Zhou，Longxi,Li，Zhongxiao,Zhou，Juexiao,et al. A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis[J]. IEEE Transactions on Medical Imaging,2020,39(8):2638-2652.

Zhou，Longxi.,Li，Zhongxiao.,Zhou，Juexiao.,Li，Haoyang.,Chen，Yupeng.,...&Gao，Xin.(2020).A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis.IEEE Transactions on Medical Imaging,39(8),2638-2652.

Zhou，Longxi,et al."A Rapid, Accurate and Machine-Agnostic Segmentation and Quantification Method for CT-Based COVID-19 Diagnosis".IEEE Transactions on Medical Imaging 39.8(2020):2638-2652.