Abstract：
:In this paper, we propose a robust wavelet domain method for noise filtering in medical images. The proposed method adapts itself to various types of image noise as well as to the preference of the medical expert; a single parameter can be used to balance the preservation of (expert-dependent) relevant details against the degree of noise reduction. The algorithm exploits generally valid knowledge about the correlation of significant image features across the resolution scales to perform a preliminary coefficient classification. This preliminary coefficient classification is used to empirically estimate the statistical distributions of the coefficients that represent useful image features on the one hand and mainly noise on the other. The adaptation to the spatial context in the image is achieved by using a wavelet domain indicator of the local spatial activity. The proposed method is of low complexity, both in its implementation and execution time. The results demonstrate its usefulness for noise suppression in medical ultrasound and magnetic resonance imaging. In these applications, the proposed method clearly outperforms single-resolution spatially adaptive algorithms, in terms of quantitative performance measures as well as in terms of visual quality of the images.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Pizurica A,Philips W,Lemahieu I,Acheroy Mdoi
10.1109/TMI.2003.809588subject
Has Abstractpub_date
2003-03-01 00:00:00pages
323-31issue
3eissn
0278-0062issn
1558-254Xjournal_volume
22pub_type
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