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    Abstract
2012 (Vol. 4, Issue: 18)
Article Information:

Micro Calcification Clusters Detection by Using Gaussian Markov Random Fields Representation

Xinsheng Zhang, Zhengshan Luo and Minghu Wang
Corresponding Author:  Xinsheng Zhang 

Key words:  Detection, feature representation, GMRFs, mammograms, mirocalcification clusters, ,
Vol. 4 , (18): 3425-3431
Submitted Accepted Published
April 17, 2012 May 18, 2012 September 15, 2012
Abstract:

In order to develop an accurate computer-aided diagnosis system for the automatic detection of microcalcification clusters in mammograms. In this study, we presented a new microcalcification clusters detection method by using Gaussian Markov Random Fields (GMRFs) representation. The design and evaluation of the algorithm involved three main phases. In the first phase of the algorithm, a training dataset is employed to train and get the GMRF texture features of each image block and then the cluster center and bias are obtained. In the second phase of the algorithm, we use GMRFs to get it texture feature with a given image block . And finally, the distance between the given image block GMRFs features and the cluster center to make a decision whether it contains a microcalcification cluster or not.
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  Cite this Reference:
Xinsheng Zhang, Zhengshan Luo and Minghu Wang, 2012. Micro Calcification Clusters Detection by Using Gaussian Markov Random Fields Representation.  Research Journal of Applied Sciences, Engineering and Technology, 4(18): 3425-3431.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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