Mammography is the most effective method for early detection of breast diseases. However, the typical diagnostic signs, such as masses and microcalcifications, are difficult to be detected because mammograms are low contrast and noisy images. In this paper, we present an algorithm for mammographic images enhancement and denoising based on the wavelet transform. In particular, we develop an adaptive procedure to perform an optimal denoising using a local iterative fuzzy noise variance estimation. Moreover, the degree of enhancement is adaptively tuned at each scale. The proposed algorithm has been tested on phantom and clinical images.
Wavelet based adaptive algorithm for mammographic images enhancement and denoising
2005-01-01
469159 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Wavelet Based Adaptive Algorithm for Mammographic Images Enhancement and Denoising
British Library Conference Proceedings | 2005
|Adaptive feature enhancement for mammographic images with wavelet multiresolution analysis
British Library Online Contents | 1997
|Wavelet transform approach to adaptive image denoising and enhancement
British Library Online Contents | 2004
|Adaptive wavelet domain thresholding denoising [5253-51]
British Library Conference Proceedings | 2003
|British Library Online Contents | 2013
|