ACSN: Attention capsule sampling network for diagnosing COVID-19 based on chest CT scans.

ABSTRACT: Automated diagnostic techniques based on computed tomography (CT) scans of the chest for the coronavirus disease (COVID-19) help physicians detect suspected cases rapidly and precisely, which is critical in providing timely medical treatment and preventing the spread of epidemic outbreaks. Existing capsule networks have played a significant role in automatic COVID-19 detection systems based on small datasets. However, extracting key slices is difficult because CT scans typically show many scattered lesion sections. In addition, existing max pooling sampling methods cannot effectively fuse the features from multiple regions. Therefore, in this study, we propose an attention capsule sampling network (ACSN) to detect COVID-19 based on chest CT scans. A key slices enhancement method is used to

SUBMITTER: Wen C 

PROVIDER: S-EPMC9678829 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature