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Methods towards the Classification of Clustered Microcalcification

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IJCA Special Issue on Advanced Computing and Communication Technologies for HPC Applications
© 2012 by IJCA Journal
ACCTHPCA - Number 3
Year of Publication: 2012
Authors:
S. Narasimhamurthy
Arun Kumar
H. S. Sheshadri

S Narasimhamurthy, Arun Kumar and H S Sheshadri. Article: Methods towards the Classification of Clustered Microcalcification. IJCA Special Issue on Advanced Computing and Communication Technologies for HPC Applications ACCTHPCA(3):35-38, July 2012. Full text available. BibTeX

@article{key:article,
	author = {S. Narasimhamurthy and Arun Kumar and H. S. Sheshadri},
	title = {Article: Methods towards the Classification of Clustered Microcalcification},
	journal = {IJCA Special Issue on Advanced Computing and Communication Technologies for HPC Applications},
	year = {2012},
	volume = {ACCTHPCA},
	number = {3},
	pages = {35-38},
	month = {July},
	note = {Full text available}
}

Abstract

Breast cancer is one of the leading causes of death among the women. Mammogram analysis is the most effective method that helps in the early detection of breast cancer. Microcalcification, masses, and architectural detection in the mammogram plays an important role in the later stages of diagnosis. In this paper we propose an effective method for the detection and classification of clustered microcalcification. We applied the proposed method in the MIAS datasets and found the effectiveness in the detection and classification of clustered microcalcification. We also brief out in this article the methods adopted to select the features for clustered microcalcification and technique to handle the class imbalance specific to microcalcification classification problem.

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