Unknown

Dataset Information

0

Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography.


ABSTRACT: Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVID19) pneumonia. We aimed to construct a system based on deep learning for detecting COVID-19 pneumonia on high resolution CT. For model development and validation, 46,096 anonymous images from 106 admitted patients, including 51 patients of laboratory confirmed COVID-19 pneumonia and 55 control patients of other diseases in Renmin Hospital of Wuhan University were retrospectively collected. Twenty-seven prospective consecutive patients in Renmin Hospital of Wuhan University were collected to evaluate the efficiency of radiologists against 2019-CoV pneumonia with that of the model. An external test was conducted in Qianjiang Central Hospital to estimate the system's robustness. The model achieved a per-patient accuracy of 95.24% and a per-image accuracy of 98.85% in internal retrospective dataset. For 27 internal prospective patients, the system achieved a comparable performance to that of expert radiologist. In external dataset, it achieved an accuracy of 96%. With the assistance of the model, the reading time of radiologists was greatly decreased by 65%. The deep learning model showed a comparable performance with expert radiologist, and greatly improved the efficiency of radiologists in clinical practice.

SUBMITTER: Chen J 

PROVIDER: S-EPMC7645624 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

altmetric image

Publications


Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVID19) pneumonia. We aimed to construct a system based on deep learning for detecting COVID-19 pneumonia on high resolution CT. For model development and validation, 46,096 anonymous images from 106 admitted patients, including 51 patients of laboratory confirmed COVID-19 pneumonia and 55 control patients of other diseases in Renmin Hospital of Wuhan University were retrospectively collected. Twenty  ...[more]

Similar Datasets

| S-EPMC7886892 | biostudies-literature
| S-EPMC7411489 | biostudies-literature
| S-EPMC7705757 | biostudies-literature
| S-EPMC7175452 | biostudies-literature
| S-EPMC8111058 | biostudies-literature
| S-EPMC8285253 | biostudies-literature
| S-EPMC7447615 | biostudies-literature
| S-EPMC8132943 | biostudies-literature
| S-EPMC7331494 | biostudies-literature
| S-EPMC8138051 | biostudies-literature