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Automated background segmentation for Rician noise estimation of noisy MR images


Tran, VH and Jiang, D, Automated background segmentation for Rician noise estimation of noisy MR images, Proceedings of CIBEC2012, 20-22 December, Cairo, Egypt, pp. 150-153. ISBN 978-1-4673-2800-5 (2012) [Refereed Conference Paper]

Copyright Statement

Copyright 2012 IEEE

DOI: doi:10.1109/CIBEC.2012.6473333


The accurate estimation of Rician noise standard deviation is necessary for effective MR image denoising. In this short paper, we show that background segmentation is desirable for an accurate estimation of Rician noise parameter. Motivated by that observation an automated background segmentation algorithm is developed by combining morphological operations and active contour model in order to get more desired results. A test set MR images on 62 slices of human knee is used for illustration purpose. The proposed method is compared with some existing noise estimation methods and is shown to produce more accurate results.

Item Details

Item Type:Refereed Conference Paper
Keywords:MRI, segmentation, Rician noise, active contour method
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Image processing
Objective Division:Health
Objective Group:Clinical health
Objective Field:Diagnosis of human diseases and conditions
UTAS Author:Tran, VH (Mr Vinh Hoang Tran)
UTAS Author:Jiang, D (Dr Danchi Jiang)
ID Code:80877
Year Published:2012
Deposited By:Engineering
Deposited On:2012-11-14
Last Modified:2018-03-28
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