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Authors
Affiliations
1 Department of Electronics and Communication Engineering, Coimbatore Institute of Technology, Tamil Nadu, IN
2 Department of Electrical and Electronics Engineering, PSG college of Technology, Tamil Nadu, IN
3 Department of Electrical and Electronics Engineering, Velalar College of Engineering & Technology, Tamil Nadu, IN
Source
ICTACT Journal on Image and Video Processing, Vol 1, No 2 (2010), Pagination: 99-104
Abstract
Mammography is the most efficient method for breast cancer early detection. Clusters of microcalcifications are the early sign of breast cancer and their detection is the key to improve prognosis of breast cancer. Microcalcifications appear in mammogram image as tiny localized granular points, which is often difficult to detect by naked eye because of their small size. Automatic and accurately detection of microcalcifications has received much more attention from radiologists and physician. An efficient method for automatic detection of clustered microcalcifications in digitized mammograms is the use of Computer Aided Diagnosis (CAD) systems. This paper presents a one dimensional wavelet-based multiscale products scheme for microcalcification detection in mammogram images. The detection of microcalcifications were achieved by decomposing the each line of mammograms by 1D wavelet transform into different frequency sub-bands, suppressing the low-frequency subband, and finally reconstructing the mammogram from the subbands containing only significant high frequencies features. The significant features are obtained by multiscale products. Preliminary results indicate that the proposed scheme is better in suppressing the background and detecting the microcalcification clusters than any other wavelet decomposition methods.
Keywords
Computer Aided Diagnosis (CAD), One Dimensional Wavelet Transform, Multiscale Product, Microcalcification Detection.
