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Abstract
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Article Information:
Micro Calcification Clusters Detection by Using Gaussian Markov Random Fields Representation
Xinsheng Zhang, Zhengshan Luo and Minghu Wang
Corresponding Author: Xinsheng Zhang
Submitted: April 17, 2012
Accepted: May 18, 2012
Published: September 15, 2012 |
Abstract:
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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.
Key words: Detection, feature representation, GMRFs, mammograms, mirocalcification clusters, ,
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Cite this Reference:
Xinsheng Zhang, Zhengshan Luo and Minghu Wang, . Micro Calcification Clusters Detection by Using Gaussian Markov Random Fields Representation. Research Journal of Applied Sciences, Engineering and Technology, (18): 3425-3431.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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