查看文章

Chest X-ray images are among the most common diagnostic tools for detecting and managing bronchopneumonia and lung abnormalities, such as those caused by COVID-19. However, interpreting these images requires significant expertise, and misinterpretations can result in false negatives or positives. Deep learning techniques have recently been highly effective in analyzing medical images, including chest X-rays. In this study, we propose two deep learning approaches to classify and localize different abnormalities, including COVID-19, on chest X-rays, which include multi-classification and object detection models that can identify and localize the presence of disease as other common abnormalities. The proposed models are trained on a large dataset of chest X-ray images from sick people (including COVID-19 patients) and validated on an independent test set. Compared to single object models, this paper …