A novel deep learning-based method for COVID-19 pneumonia detection from CT images

BMC Medical Informatics and Decision Making

卷:22

Research

Xin Liao¹  Yuhao Sun¹  Jingshu Chi²  Canxia Xu²  Ju Luo² 

[1] College of Computer Science and Electronic Engineering, Hunan University, Changsha, China;

[2] Third Xiangya Hospital, Central South University, NO.138, Tongzipo Road, 410013, Changsha, Hunan, China;

关键词: Artificial intelligence;    Deep learning;    COVID-19;    Community acquired pneumonia;    CT image;   

DOI  :  10.1186/s12911-022-02022-1

 received in 2022-04-05, accepted in 2022-10-17,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundThe sensitivity of RT-PCR in diagnosing COVID-19 is only 60–70%, and chest CT plays an indispensable role in the auxiliary diagnosis of COVID-19 pneumonia, but the results of CT imaging are highly dependent on professional radiologists.AimsThis study aimed to develop a deep learning model to assist radiologists in detecting COVID-19 pneumonia.MethodsThe total study population was 437. The training dataset contained 26,477, 2468, and 8104 CT images of normal, CAP, and COVID-19, respectively. The validation dataset contained 14,076, 1028, and 3376 CT images of normal, CAP, and COVID-19 patients, respectively. The test set included 51 normal cases, 28 CAP patients, and 51 COVID-19 patients. We designed and trained a deep learning model to recognize normal, CAP, and COVID-19 patients based on U-Net and ResNet-50. Moreover, the diagnoses of the deep learning model were compared with different levels of radiologists.ResultsIn the test set, the sensitivity of the deep learning model in diagnosing normal cases, CAP, and COVID-19 patients was 98.03%, 89.28%, and 92.15%, respectively. The diagnostic accuracy of the deep learning model was 93.84%. In the validation set, the accuracy was 92.86%, which was better than that of two novice doctors (86.73% and 87.75%) and almost equal to that of two experts (94.90% and 93.88%). The AI model performed significantly better than all four radiologists in terms of time consumption (35 min vs. 75 min, 93 min, 79 min, and 82 min).ConclusionThe AI model we obtained had strong decision-making ability, which could potentially assist doctors in detecting COVID-19 pneumonia.

【 授权许可】

CC BY   
© The Author(s) 2022

【 图 表 】

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