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Signal dependent Rician noise denoising using nonlinear filter

journal contribution
posted on 2023-05-17, 19:57 authored by Aarya, I, Jiang, D, Timothy GaleTimothy Gale
MR images are increasingly used for diagnostic and surgical procedures, as they offer better soft tissue contrast and advanced imaging capabilities. Similar to other imaging modalities, MR images are also subjected to various forms of noises and artifacts. The noise affecting MRI images is known as Rician noise and displays a nonlinear and signal dependent behavior. In this paper we propose a nonlinear filtering method for Rician noise denoising. Nonlinear filters are more capable in addressing signal dependent behavior of noise and offer good denoising with better edge preserving capabilities. A nonlinear filter based on homomorphic filter characteristics has been designed to address Rician noise in MR images. The proposed filter has been implemented on synthetic images and MR images of the articular cartilage. The efficiency of the proposed filtering method is verified by computing the PSNR and SSIM index of the image. The proposed nonlinear filter performs good denoising with improvement in the image quality as observed from the PSNR values of the image. It also offers edge preservation and can be used for both structural MRI and soft tissue study effectively.

History

Publication title

Lecture Notes on Software Engineering

Issue

4

Pagination

344-349

ISSN

2301-3559

Department/School

School of Engineering

Publisher

International Association of Computer Science and Information Technology Press (IACSIT Press)

Place of publication

Singapore

Rights statement

Copyright 2013 International Association of Computer Science and Information Technology Press

Repository Status

  • Restricted

Socio-economic Objectives

Clinical health not elsewhere classified

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