In the realm of medical image processing, noise removal remains a critical endeavor for enhancing diagnostic accuracy. The conventional filtering techniques may also enhance the prevalent noise which may induce false artifacts or may suppress the genuine ones leading to erroneous diagnosis. In this study, we propose an improved bilateral filtering technique tailored specifically for denoising medical images. This work integrates spatial and intensity parameters along with entropy as a key factor to preserve the information contained during the denoising process. Furthermore, implementation of the denoising process for selective and adaptive regions of interest (ROI) has been incorporated. Effectiveness of the proposed method has been evaluated through various performance measures and compared with the state-of-the-art techniques. The proposed EEBF filter outperforms in terms of quality as well as time efficiency.