Adaptive Rician denoising with edge preservation for MR images of the articular cartilage

Abstract

MR image offers better soft tissue contrast which makes it advantageous for cartilage diagnosis for patients suffering from Osteoarthritis. But magnitude MR images are susceptible to Rician noise which affects image quality leading to incorrect diagnosis. In this paper we propose a novel Rician denoising procedure with edge preservation capability. An adaptive filter with Brown–Forsythe statistical criterion has been implemented to avoid excessive filtering near the edges. Denoising is achieved using a linear minimum mean square estimate of the regional sample, obtained using a modified non-local means estimate within the neighbourhood of the image. The proposed filter was implemented on MR images of the knee, synthetic and a phantom. The efficiency of the denoising procedure was determined using signal-to-noise ratio, root mean square error, quality index based on local variance and contrast-to-noise ratio between true and denoised images of the cartilage. The method was also compared with other existing Rician denoising procedures and showed improved image contrast with edge preservation ability.