Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label

Chuansheng Zheng; Xianbo Deng; Qing Fu; Qiang Zhou; Jiapei Feng; Hui Ma; Wenyu Liu; Xinggang Wang

Between Dec. 13, 2019 to Feb. 6, 2020, we searched unenhanced chest CT scans of patients with suspected COVID-19 from the picture archiving and communication system (PACS) of radiology department (Union Hospital, Tongji Medical College, Huazhong University of Science and Technology). Finally, 540 patients (mean age, 42.5±16.1 years; range, 3-81 years, male 226, female 314) were enrolled into this study, including 313 patients (mean age, 50.7±14.7 years; range, 8-81 years; male 138, female 175) with clinical diagnosed COVID-19 (COVID-positive group) and 229 patients (mean age, 31.2±10.0 years; range, 3-69 years; male 88, female 141) without COVID-19 (COVID-negative group). There was no significant difference in sex between the two groups (χ 2 =1.744; P=0.187), age in COVIDpositive group significantly higher than that of COVID-negative group (t=17.09; P<0.001). The main clinical symptoms for these patients were fever, cough, fatigue, and diarrhea. Of all the patients, two were included by both groups due to the first and second follow-up CT scans. The first case (female, year 66) was diagnosed as COVID-19 negative on Jan 24, 2020, then changed into COVID-positive on Feb 6, 2020; the second case (female, year 23) was diagnosed as COVID-19 positive on Jan 24, 2020, then changed into COVID-negative on Feb 3, 2020. All the CT volumes scanned on and before Jan 23, 2020, were assigned for deep learning training, and all the CT volumes scanned after Jan 23, 2020, were assigned for deep learning testing.