Medical image denoising based on adaptive thresholding in contourlet domain

Substantial noises have been added in medical images during its acquisition which adversely affects its quality and hence may leads to misdiagnosis. Therefore it is necessary to process these images in order to reduce noises before their interpretation and analysis. In this paper, we proposed a Cont...

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Bibliographic Details
Published in2012 5th International Conference on Biomedical Engineering and Informatics pp. 313 - 318
Main Authors Kazmi, Majida, Aziz, Arshad, Akhtar, Pervez, Maftun, Aliza, Afaq, Wasay Bin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
Subjects
adaptive threshold
Bayes methods
bayes shrink
Biomedical imaging
Computed tomography
contourlet transform
Filter banks
gaussian smoothing
Image reconstruction
Magnetic resonance imaging
Noise
Noise reduction
Smoothing methods
soft thresholding
Thresholding (Imaging)
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Summary:Substantial noises have been added in medical images during its acquisition which adversely affects its quality and hence may leads to misdiagnosis. Therefore it is necessary to process these images in order to reduce noises before their interpretation and analysis. In this paper, we proposed a Contourlet based adaptive threshold method to reduce the noise of MRI images. We have compared the proposed method with other conventional de noising methods, and found that our method outperforms in terms of PSNR. Visual quality of images after denoising by using our proposed method is also superior as compare to other methods.
ISBN:9781467311830
1467311839
DOI:10.1109/BMEI.2012.6512939