The research evaluates different image enhancement approaches regarding their impact on deep learning algorithms which detect body regions in X-ray scans. We analyze how Bilateral Filtering as well as Contrast Limited Adaptive Histogram Equalization (CLAHE) and Wavelet Denoising and Super-Resolution influence X-ray image quality which subsequently impacts Convolutional Neural Networks (CNNs) classification results. The evaluation demonstrates Bilateral Filtering delivers superior performance than other enhancement processes according to PSNR and SSIM evaluations on LEG, CTScan and Chest X-ray datasets. The experimental results for the LEG dataset demonstrated Bilateral Filtering produced a h... More >