A robust edge preserving bilateral filter for ultrasound kidney image

Abstract

Objective: The speckle noise reduction is an important preprocessing step, normally performed to improve the segmentation of kidney images for the diagnosis of stones' presence or its size. The bilateral filter is a robust method for noise reduction with edge preservation. An attempt is made in this work to analyze the effectiveness of the bilateral filter for speckle reduction in ultrasound kidney images. Methods/Statistical Analysis: An open source software Fijiis used to develop the filtering algorithms for ultrasound kidney image. The bilateral filter performance is compared with familiar speckle filters named median filter, Speckle Reducing Anisotropic Diffusion (SRAD) filter and Non-Local Mean (NLM) filter. The authors have selected mainly Root Mean Square Error (RMSE) for image quality analysis, Signal to Noise Ratio (SNR) for comparison of noise with useful signal strength, Peak Signal to Noise Ratio (PSNR) for maximum amplitude of signal, Mean Absolute Error (MAE) for overall performance and Structural Similarity Index Measure (SSIM) for testing bilateral filter on kidney images. The statistical measures also calculated to distinguish the filter performances. Findings: The bilateral filter performance is proven as an effective method for speckle reduction in ultrasound kidney stone detection applications than the existing methods through quantitative and statistical analysis. Application/Improvement: The bilateral filter can offer better segmentation of kidney stone due to its effective speckle reduction.