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Early Detection of Breast Cancer using Self Similar Fractal Method

International Journal of Computer Applications
© 2010 by IJCA Journal
Number 4 - Article 8
Year of Publication: 2010
Bhagwati Charan Patel
Dr. G.R.Sinha

Bhagwati Charan Patel and Dr. G.R.Sinha. Article:Early Detection of Breast Cancer using Self Similar Fractal Method. International Journal of Computer Applications 10(4):39–43, November 2010. Published By Foundation of Computer Science. BibTeX

	author = {Bhagwati Charan Patel and Dr. G.R.Sinha},
	title = {Article:Early Detection of Breast Cancer using Self Similar Fractal Method},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {10},
	number = {4},
	pages = {39--43},
	month = {November},
	note = {Published By Foundation of Computer Science}


Breast cancer is one of the major causes of death among women. Small clusters of micro calcifications appearing as collection of white spots on mammograms show an early warning of breast cancer. Early detection performed on X-ray mammography is the key to improve breast cancer diagnosis. Image segmentation consists in finding the characteristic entities of an image, either by their contours (edges) or by the region they lie in. Our aim in this paper is to present a method for medical image enhancement based on the well established concept of fractal derivatives and selecting image processing techniques like segmentation of an image with self similar properties. The concept of a fractal is most often associated with geometrical objects satisfying two criteria: self-similarity and fractional dimensionality. The method was tested over several images of image databases taken from BSR APPOLO for cancer research and diagnosis, India.


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