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Proceedings Paper

A new study on mammographic image denoising using multiresolution techniques
Author(s): Min Dong; Ya-Nan Guo; Yi-De Ma; Yu-run Ma; Xiang-yu Lu; Ke-ju Wang
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Paper Abstract

Mammography is the most simple and effective technology for early detection of breast cancer. However, the lesion areas of breast are difficult to detect which due to mammograms are mixed with noise. This work focuses on discussing various multiresolution denoising techniques which include the classical methods based on wavelet and contourlet; moreover the emerging multiresolution methods are also researched. In this work, a new denoising method based on dual tree contourlet transform (DCT) is proposed, the DCT possess the advantage of approximate shift invariant, directionality and anisotropy. The proposed denoising method is implemented on the mammogram, the experimental results show that the emerging multiresolution method succeeded in maintaining the edges and texture details; and it can obtain better performance than the other methods both on visual effects and in terms of the Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Structure Similarity (SSIM) values.

Paper Details

Date Published: 8 December 2015
PDF: 7 pages
Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 987518 (8 December 2015); doi: 10.1117/12.2228704
Show Author Affiliations
Min Dong, Lanzhou Univ. (China)
Ya-Nan Guo, Lanzhou Univ. (China)
Yi-De Ma, Lanzhou Univ. (China)
Yu-run Ma, Lanzhou Univ. (China)
Xiang-yu Lu, Lanzhou Univ. (China)
Ke-ju Wang, Lanzhou Univ. (China)


Published in SPIE Proceedings Vol. 9875:
Eighth International Conference on Machine Vision (ICMV 2015)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev, Editor(s)

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