Author: Chuansheng Zheng; Xianbo Deng; Qing Fu; Qiang Zhou; Jiapei Feng; Hui Ma; Wenyu Liu; Xinggang Wang
Title: Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label Document date: 2020_3_17
ID: ll4rxd9p_1
Snippet: huge amount of efforts for radiologists, which is not acceptable when COVID-19 is spreading fastly and there are great shortages for radiologists. Thus, performing COVID-19 detection in a weakly-supervised manner is of great importance. One of the simplest labels for COVID-19 detection is the patient-level, i.e., indicating the patient is COVID-19 positive or negative. Therefore, aim of current study was to investigate the potential of a deep lea.....
Document: huge amount of efforts for radiologists, which is not acceptable when COVID-19 is spreading fastly and there are great shortages for radiologists. Thus, performing COVID-19 detection in a weakly-supervised manner is of great importance. One of the simplest labels for COVID-19 detection is the patient-level, i.e., indicating the patient is COVID-19 positive or negative. Therefore, aim of current study was to investigate the potential of a deep learning-based model for automatic COVID-19 detection on chest CT volumes using the weak patient-level label, for the sake of rapid diagnosis of COVID-19 at this critical situation to help to counter this outbreak, especially within Wuhan, Hubei province, China.
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