Robust Rician noise estimation for MR images.

Abstract : In this paper, a new object-based method to estimate noise in magnitude MR images is proposed. The main advantage of this object-based method is its robustness to background artefacts such as ghosting. The proposed method is based on the adaptation of the Median Absolute Deviation (MAD) estimator in the wavelet domain for Rician noise. The MAD is a robust and efficient estimator initially proposed to estimate Gaussian noise. In this work, the adaptation of MAD operator for Rician noise is performed by using only the wavelet coefficients corresponding to the object and by correcting the estimation with an iterative scheme based on the SNR of the image. During the evaluation, a comparison of the proposed method with several state-of-the-art methods is performed. A quantitative validation on synthetic phantom with and without artefacts is presented. A new validation framework is proposed to perform quantitative validation on real data. The impact of the accuracy of noise estimation on the performance of a denoising filter is also studied. The results obtained on synthetic images show the accuracy and the robustness of the proposed method. Within the validation on real data, the proposed method obtained very competitive results compared to the methods under study.
Complete list of metadatas

Cited literature [40 references]  Display  Hide  Download

https://www.hal.inserm.fr/inserm-00486495
Contributor : Pierrick Coupé <>
Submitted on : Tuesday, May 25, 2010 - 9:44:33 PM
Last modification on : Thursday, February 7, 2019 - 5:01:23 PM
Long-term archiving on : Thursday, December 1, 2016 - 4:07:26 AM

File

FinalVersionResub_last.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Pierrick Coupé, José Manjón, Elias Gedamu, Douglas Arnold, Montserrat Robles, et al.. Robust Rician noise estimation for MR images.. Medical Image Analysis, Elsevier, 2010, 14 (4), pp.483-93. ⟨10.1016/j.media.2010.03.001⟩. ⟨inserm-00486495⟩

Share

Metrics

Record views

996

Files downloads

2375