CT Image Denoising Using Bilateral Filter and Convolutional Neural Network

This article discusses how to improve the quality of clinical images, especially those obtained by techniques such as X-ray, ultrasound, and angiography. During the capture process, this image often contains noise that can distort and degrade the quality of the image. In this paper, the author proposes a noise reduction method for Computed Tomography (CT) images using Bilateral Filter and Convolutional Neural Networks (CNNs). What distinguishes this approach is that it does not depend on access to original projection data, which can be difficult to obtain in some cases. The research results show that this method provides a significant improvement in image quality in terms of visual evaluation and quantitative analysis. This means reducing noise and improving image clarity while preserving important diagnostic information. In fact, this paper provides a new and promising method to improve clinical images, which can benefit medical professionals in making more accurate diagnoses and improving patient care.