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Fractal analysis and classification of breast masses using the power spectra of signatures of contours

[+] Author Affiliations
Rangaraj M. Rangayyan

University of Calgary, Department of Electrical and Computer Engineering, Schulich School of Engineering, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada

Faraz Oloumi

University of Calgary, Department of Electrical and Computer Engineering, Schulich School of Engineering, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada

J. Electron. Imaging. 21(2), 023018 (Jun 22, 2012). doi:10.1117/1.JEI.21.2.023018
History: Received September 23, 2011; Revised April 16, 2012; Accepted May 4, 2012
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Abstract.  The contours of benign masses and malignant tumors in mammograms and other types of breast images differ substantially in their shape and complexity; the former are usually round and smooth, whereas the latter are typically spiculated and irregular. We demonstrate the usefulness of fractal analysis via a frequency domain approach applied to one-dimensional signatures of the two-dimensional contours of breast masses in mammograms. The 1/f model related to fractional Brownian motion was applied via power spectral analysis of signatures to estimate the fractal dimension. Experiments with a dataset of 111 contours, including those of 65 benign masses and 46 malignant tumors, indicated a high classification performance of 0.8962 in terms of the area under the receiver-operating characteristic curve. The method should be useful in computer-aided diagnosis of breast cancer.

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Citation

Rangaraj M. Rangayyan and Faraz Oloumi
"Fractal analysis and classification of breast masses using the power spectra of signatures of contours", J. Electron. Imaging. 21(2), 023018 (Jun 22, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.2.023018


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