Publications by authors named "Uzair Khurshid"
Article Synopsis
- - The study focuses on classifying chest X-ray images of COVID-19, SARS, and MERS using deep learning, particularly convolutional neural networks (CNNs), analyzing a new database of images called QU-COVID-family which includes 423 COVID-19, 144 MERS, and 134 SARS images.
- - A recognition system was developed to segment lung regions and categorize the images, finding that the InceptionV3 model performed the best, achieving high sensitivities in classifying the diseases using both plain and segmented X-rays.
- - While segmentation led to a decrease in classification performance compared to plain X-rays, it provided more reliable results by focusing the network's learning on the critical areas of the lungs.
The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 on pulmonary tissues, chest radiographic imaging has become a necessity for screening and monitoring the disease. Numerous studies have proposed Deep Learning approaches for the automatic diagnosis of COVID-19.
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