DocumentCode :
1195963
Title :
Phase-Adaptive Superresolution of Mammographic Images Using Complex Wavelets
Author :
Wong, Alexander ; Scharcanski, Jacob
Author_Institution :
Syst. Design Eng., Univ. of Waterloo, Waterloo, ON
Volume :
18
Issue :
5
fYear :
2009
fDate :
5/1/2009 12:00:00 AM
Firstpage :
1140
Lastpage :
1146
Abstract :
This correspondence describes a new superresolution approach for enhancing the resolution of mammographic images using complex wavelet frequency information. This method allows regions of interest of a mammographic image to be viewed in enhanced resolution while reducing the patient exposure to radiation. The proposed method exploits the structural characteristics of breast tissues being imaged and produces higher resolution mammographic images with sufficient visual fidelity that fine image details can be discriminated more easily. In our approach, the superresolution problem is formulated as a constrained optimization problem using a third-order Markov prior model and adapts the priors based on the phase variations of the low-resolution mammographic images. Experimental results indicate the proposed method is more effective at preserving the visual information when compared with existing resolution enhancement methods.
Keywords :
Markov processes; biological tissues; cancer; diagnostic radiography; image enhancement; image resolution; mammography; medical image processing; wavelet transforms; breast tissue; complex wavelet frequency information; constrained optimization problem; mammographic image; patient exposure; phase-adaptive superresolution enhancement; third-order Markov prior model; visual information; Adaptive; mammography; phase; superresolution; Algorithms; Breast Neoplasms; Female; Humans; Mammography; Markov Chains; Models, Biological; Radiographic Image Enhancement;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2009.2013077
Filename :
4802019
Link To Document :
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