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Proceedings Paper

Super-resolution reconstruction of compressed sensing mammogram based on contourlet transform
Author(s): Yan Shen; Houjin Chen; Chang Yao; Zhijun Qiao
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Paper Abstract

Calcification detection in mammogram is important in breast cancer diagnosis. A super-resolution reconstruction method is proposed to reconstruct mammogram image from one single low resolution mammogram based on the compressed sensing by the contourlet transform. The initial estimation of the super-resolution mammogram is obtained by the interpolation method of the low resolution mammogram reconstructed by compressed sensing, then contourlet transform is applied respectively to the initial estimation and the reconstructed low resolution mammogram. From the statistical characteristics of the mutiscale frequency bands between the initial estimation and the reconstructed low resolution mammogram, the thresholds are estimated to integrate the high frequency of the initial estimation and the low frequency of the reconstructed low resolution mammogram. The super-resolution mammogram is achieved through the reconstruction of contourlet inverse transform. The proposed method can retrieve some details of the low resolution images. The calcification in mammogram can be detected efficiently.

Paper Details

Date Published: 29 May 2013
PDF: 6 pages
Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500M (29 May 2013); doi: 10.1117/12.2019037
Show Author Affiliations
Yan Shen, Beijing Jiaotong Univ. (China)
Houjin Chen, Beijing Jiaotong Univ. (China)
Chang Yao, Beijing Jiaotong Univ. (China)
Zhijun Qiao, The Univ. of Texas-Pan American (United States)


Published in SPIE Proceedings Vol. 8750:
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
Harold H. Szu, Editor(s)

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