Abstract
COVID-19 is a fast-spreading pandemic, and early detection is crucial for stopping the spread of infection. Lung images are used in the detection of coronavirus infection. Chest X-ray (CXR) and computed tomography (CT) images are available for the detection of COVID-19. Deep learning methods have been proven efficient and better performing in many computer vision and medical imaging applications. In the rise of the COVID pandemic, researchers are using deep learning methods to detect coronavirus infection in lung images. In this paper, the currently available deep learning methods that are used to detect coronavirus infection in lung images are surveyed. The available methodologies, public datasets, datasets that are used by each method and evaluation metrics are summarized in this paper to help future researchers. The evaluation metrics that are used by the methods are comprehensively compared.
| Original language | English |
|---|---|
| Article number | 105233 |
| Journal | Computers in Biology and Medicine |
| Volume | 143 |
| DOIs | |
| Publication status | Published - Apr 2022 |
| Externally published | Yes |
Keywords
- COVID-19 detection
- Coronavirus pandemic
- DL-Based COVID-19 detection
- Lung image classification
- Medical image processing
ASJC Scopus subject areas
- Health Informatics
- Computer Science Applications
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