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Robust framework for COVID-19 identication from a multicenter dataset of chest CT scans

Author(s): Khademi S; Heidarian S; Afshar P; Enshaei N; Naderkhani F; Rafiee MJ; Oikonomou A; Shafiee A; Babaki Fard F; Plataniotis KN; Mohammadi A; ...

The main objective of this study is to develop a robust deep learning-based framework to distinguish COVID-19, Community-Acquired Pneumonia (CAP), and Normal cases based on volumetric chest CT scan ...

Article GUID: 36862633


Human-level COVID-19 diagnosis from low-dose CT scans using a two-stage time-distributed capsule network

Author(s): Afshar P; Rafiee MJ; Naderkhani F; Heidarian S; Enshaei N; Oikonomou A; Babaki Fard F; Anconina R; Farahani K; Plataniotis KN; Mohammadi A; ...

Reverse transcription-polymerase chain reaction is currently the gold standard in COVID-19 diagnosis. It can, however, take days to provide the diagnosis, and false negative rate is relatively high ...

Article GUID: 35318368


COVID-rate: an automated framework for segmentation of COVID-19 lesions from chest CT images

Author(s): Enshaei N; Oikonomou A; Rafiee MJ; Afshar P; Heidarian S; Mohammadi A; Plataniotis KN; Naderkhani F; ...

Novel Coronavirus disease (COVID-19) is a highly contagious respiratory infection that has had devastating effects on the world. Recently, new COVID-19 variants are emerging making the situation mo ...

Article GUID: 35217712


COVID-FACT: A Fully-Automated Capsule Network-Based Framework for Identification of COVID-19 Cases from Chest CT Scans

Author(s): Heidarian S; Afshar P; Enshaei N; Naderkhani F; Rafiee MJ; Babaki Fard F; Samimi K; Atashzar SF; Oikonomou A; Plataniotis KN; Mohammadi A; ...

The newly discovered Coronavirus Disease 2019 (COVID-19) has been globally spreading and causing hundreds of thousands of deaths around the world as of its first emergence in late 2019. The rapid o ...

Article GUID: 34113843


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