Abstract
A method that performs multiresolution enhancement, adaptive to breast components, for optimal visualization of the entire breast area is presented. The method includes an edge detection step to distinguish breast area from mammogram background and employs Gaussian mixture modeling to segment breast components (uncompressed fat, fat and dense). The original image is decomposed using a redundant discrete wavelet transform and magnitude coefficients corresponding to each breast component are linearly mapped for contrast enhancement. Coefficient mapping is controlled by a gain factor provided by the parameters of the modeled breast components. The processed image is derived by reconstruction of the modified wavelet coefficients. The algorithm is compared with two enhancement methods proposed for soft-copy display, in a dataset of 68 mammograms containing lesions. The proposed method demonstrates increased performance in accentuating lesions embedded in fatty or dense parenchyma, as well as in visualization of anatomical features in the entire breast area.
Keywords
- Gaussian Mixture Modeling
- Gain Factor
- Enhancement Method
- Screen Film Mammography
- Contrast Limited Adaptive Histogram Equalization
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Skiadopoulos, S., Karahaliou, A., Sakellaropoulos, F., Panayiotakis, G., Costaridou, L. (2006). Breast Component Adaptive Wavelet Enhancement for Soft-Copy Display of Mammograms. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds) Digital Mammography. IWDM 2006. Lecture Notes in Computer Science, vol 4046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11783237_74
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DOI: https://doi.org/10.1007/11783237_74
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35625-7
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