Title :
Fractal analysis of contours of breast masses in mammograms via the power spectra of their signatures
Author :
Rangayyan, Rangaraj M. ; Oloumi, Faraz ; Nguyen, Thanh M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Calgary, Calgary, AB, Canada
fDate :
Aug. 31 2010-Sept. 4 2010
Abstract :
Contours of benign breast masses and malignant tumors in mammograms 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. The 1/f model was applied to power spectra of signatures to estimate the fractal dimension. Tests with a dataset of 111 contours, including those of 65 benign masses and 46 malignant tumors, indicated a high classification performance of 0.89 in terms of the area under the receiver operating characteristic curve.
Keywords :
biological organs; cancer; edge detection; fractals; image classification; mammography; medical image processing; sensitivity analysis; tumours; benign breast mass; classification; fractal analysis; fractal dimension; frequency domain approach; malignant tumors; mammograms; power spectra; receiver operating characteristic curve; two-dimensional contours; Benign tumors; Breast; Computational modeling; Fractals; Malignant tumors; Shape; Solid modeling; Breast Neoplasms; Diagnosis, Differential; Female; Humans; Mammography; Radiographic Image Interpretation, Computer-Assisted;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5626017