Document Type
Thesis - University Access Only
Award Date
2012
Degree Name
Master of Science (MS)
Department / School
Electrical Engineering and Computer Science
First Advisor
Sung Y. Shin
Abstract
Shape is one of typical descriptions of a mammographically detected breast mass. The morphol ogical appearance is also used as a malignancy diagnosis factor. It is believed that masses appearing with very irregular shapes are highly suspicious for breast cancer, while a purely round or oval mass is likely benign. Thus, an effective irregularity measure could aid medical doctors in diagnosing. In this paper, Fourier Irregularity Index (Fu), Compactness Index (Cl), Fractal Dimension (FD) and Fourier Factor (FF) were investigated and assessed by applying them with 1304 mammograms. The result shows Fu outperforms the other methods. Furthermore, in order to achieve a higher performance, combined measures of these four methods are studied. Radial Basis Function Neural Network is employed to build classifiers that use different combinations of measures. The results show the classifier using all four measures, including F11, outperforms those classifiers using a single measure or other combinations of measures.
Library of Congress Subject Headings
Breast -- Imaging
Breast -- Cancer -- Diagnosis
Breast -- Radiography
Publisher
South Dakota State University
Recommended Citation
Zhang, Gensheng, "Fourier Irregularity Index: A New Approach to Measure Irregularity of Breast Masses in Mammograms" (2012). Electronic Theses and Dissertations. 1969.
https://openprairie.sdstate.edu/etd2/1969
Rights Statement
