Improving the Quality of Chest X-rays Through Adaptive Image Enhancement Filters (ACEF)
TL;DR
The Adaptive Chest Enhancement Filter is described, a three-stage preprocessing filter that combines image decongestion, lung-specific contrast enhancement, and tissue boundary preservation that has the highest contrast and entropy values among the filters tested.
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.