Super-resolution reconstruction of compressed sensing mammogram based on contourlet transform

Yan Shen; Houjin Chen; Chang Yao; Zhijun Qiao

doi:10.1117/12.2019037

29 May 2013 Super-resolution reconstruction of compressed sensing mammogram based on contourlet transform

Yan Shen, Houjin Chen, Chang Yao, Zhijun Qiao

Proceedings Volume 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI; 87500M (2013) https://doi.org/10.1117/12.2019037
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

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.

Citation Download Citation

Yan Shen, Houjin Chen, Chang Yao, and Zhijun Qiao "Super-resolution reconstruction of compressed sensing mammogram based on contourlet transform", Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500M (29 May 2013); https://doi.org/10.1117/12.2019037

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available