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A New Iterative Triclass Thresholding for Liver Cancer Image using BFO

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IJCA Proceedings on National Conference on Information and Communication Technologies
© 2015 by IJCA Journal
NCICT 2015 - Number 1
Year of Publication: 2015
Authors:
Uma S
Ganga T

Uma S and Ganga T. Article: A New Iterative Triclass Thresholding for Liver Cancer Image using BFO. IJCA Proceedings on National Conference on Information and Communication Technologies NCICT 2015(1):5-8, September 2015. Full text available. BibTeX

@article{key:article,
	author = {Uma S and Ganga T},
	title = {Article: A New Iterative Triclass Thresholding for Liver Cancer Image using BFO},
	journal = {IJCA Proceedings on National Conference on Information and Communication Technologies},
	year = {2015},
	volume = {NCICT 2015},
	number = {1},
	pages = {5-8},
	month = {September},
	note = {Full text available}
}

Abstract

The idea of this paper is to detect the cancer from the liver image. The shape features of the cancer region are measured and it will be used for further diagnosis. The threshold for image segmentation is obtained by using triclass thresholding method. In this method, based upon the threshold the regions are divided into 3 classes. The first and second classes are foreground and background regions. The third class is a "to-be-determined" (TBD) region. This process is done iteratively and it continued until the preset threshold value is met. To obtain the optimal threshold value this method is combined with bacterial foraging optimization and with variants of bacterial foraging optimization. The result of this method is used for further diagnosis.

References

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