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