Introducing Novel Radon-Based Transform for Disease Detection From Chest X-Ray Images
Published in 2024 6th International Conference on Pattern Analysis and Intelligent Systems (PAIS), 2024
This conference paper introduces a novel technique for feature extraction from chest X-ray (CXR) images using an advanced version of the Radon transform, termed the RadEx Transform. This new method significantly improves the accuracy of disease detection models by enhancing their learning capability through the integration of RadEx features with CXR images. The study focuses on the COVID-19 radiography dataset, demonstrating that this approach surpasses conventional techniques in terms of performance metrics x, y, and z.
The findings underscore the potential of RadEx in advancing medical image analysis and diagnostics, particularly in the accurate detection of lung diseases. This research was presented at the 2024 6th International Conference on Pattern Analysis and Intelligent Systems (PAIS) and marks a significant contribution to the field of medical imaging.
Recommended citation: Islam, A., Mohsen, F., Shah, Z., & Belhaouari, S. B. (2024). "Introducing Novel Radon-Based Transform for Disease Detection From Chest X-Ray Images." In 2024 6th International Conference on Pattern Analysis and Intelligent Systems (PAIS) (pp. 1--5). IEEE. https://doi.org/10.1109/PAIS62114.2024.10541204
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