Samarra Journal of Pure and Applied Science
Improving the Quality of Chest X-rays Through Adaptive Image Enhancement Filters (ACEF)
By Omar Mohammed Dhayef.
Abstract
Respiratory diseases are difficult to identify due to picture distortion, hence chest X-rays are commonly used to diagnose lung ailments, particularly in low-light settings. Raw radiographs frequently exhibit issues such as insufficient contrast, picture distortion, and poor tissue border definition, all of which can have a negative impact on radiographic accuracy, especially in low light. This paper describes the Adaptive Chest Enhancement Filter (ACEF), a three-stage preprocessing filter that combines image decongestion, lung-specific contrast enhancement, and tissue boundary preservation. ACEF was compared to the CLAHE and Wiener filters on 210 chest X-ray pictures obtained from a private radiology and ultrasound center. ACEF has the highest contrast (69.278) and entropy (7.773) values among the filters tested. This shows the exciting future of employing deep.
Keywords
- Ultrasound in Clinical Applications
- Open access
Source
Published in Samarra Journal of Pure and Applied Science. The abstract is shown as published and remains the work of its authors; read the full article at the source.
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