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Image Enhancement for COVID-19 X-ray Detection by Jahangir Sidiq is a document available to read on EtoBox.

What is Image Enhancement for COVID-19 X-ray Detection about?

This study investigates the impact of various image enhancement techniques on the detection of COVID-19 using a large dataset of chest X-ray images. A novel U-Net model was proposed for lung segmentation, achieving high accuracy, while the gamma correction technique outperformed others in detecting COVID-19. The findings suggest that while plain CXR images yield slightly better classification performance, segmented lung images significantly improve the reliability of network performance.

Author

Jahangir Sidiq

Language

EN