A CAD System for Breast Cancer Diagnosis Using Modified Genetic Algorithm Optimized Artificial Neural Network
In this paper, a computerized scheme for automatic detection of cancerous tumors in mammograms has been examined. Diagnosis of breast tumors at the early stage is a very difficult task as the cancerous tumors are embedded in normal breast tissue structures. This paper proposes a supervised machine learning algorithm – Modified Genetic Algorithm (MGA) tuned Artificial Neural Network for detection of tumors in mammograms. Genetic Algorithm is a population based optimization algorithm based on the principle of natural evolution. By utilizing the MGA, the parameters of the Artificial Neural Network (ANN) are optimized. To increase the detection accuracy a feature extraction methodology is used to extract the texture features of the cancerous tissues and normal tissues prior to classification. Then Modified Genetic Algorithm (MGA) tuned Artificial Neural Network classifier is applied at the end to determine whether a given input data is suspicious for tumor or not. The performance of our computerized scheme is evaluated using a database of 322 mammograms originated from MIAS databases. The result shows that the proposed algorithm has a recognition score of 97.8%.
KeywordsMicrocalcification Mammograms Computer Aided Detection Neural Network Texture Energy Measures Genetic Algorithm
Unable to display preview. Download preview PDF.
- 6.Chen, Y., Chang, C.: New Texture shape feature coding based computer aided diagnostic methods for classification of masses on mammograms. In: 26th IEEE Annual Int. Conference of the Engg. In Medicine and Biology Society IEMBS, vol. 1, pp. 1275–1281 (2004)Google Scholar
- 16.Suckling, J., Parker, J.: The Mammographic Images Analysis Society Digital Mammogram Database. In: Proc. of 2nd Int. Workshop Digital Mammography, U.K, pp. 375–378 (1994)Google Scholar
- 17.Rajasekaran, S., Vijayalakshmi Pai, G.A.: Neural Networks, Fuzzy Logic and Genetic Algorithms. Prentice Hall of India (2000)Google Scholar
- 18.Dheeba, J, Tamil Selvi, S.: Screening Mammogram Images for Abnormalities using Radial Basis Function Neural Network. In: IEEE International Conference- ICCCCT 2010, pp. 554–559 (2010)Google Scholar