9IEC: A novel method for exposer region determination in low contrast and nonuniform illumination chest X-ray imaging

Abstract

Accurate chest X-ray (CXR) image interpretation is crucial for diagnosing numerous diseases. However, CXRs often suffer from nonuniform illumination and low contrast, leading to misclassification of exposure regions, which affects diagnostic accuracy. Existing methods rely on simplistic intensity-based classification, which results in errors. To address this, we propose the 9IEC algorithm, which introduces a novel integration of intensity, entropy, and contrast to define nine subregions and improve exposure region determination. This approach enables precise image enhancement, leading to superior visual interpretation and improved diagnostic reliability. Extensive qualitative evaluations, including expert surveys, demonstrate that 9IEC outperforms state-of-the-art methods and extends its utility beyond medical imaging.