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Cancer tissues recognition system using box counting method and artificial neural network

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2 Author(s)
George, L.E. ; Dept. of Comput. Sci., Univ. of Baghdad, Baghdad, Iraq ; Mohammed, E.Z.

The research presented in this paper was aimed to develop a recognition system for microscopic images of breast tissues samples. The system should classify breast tissues as malignant or not, or identifying their malignancy types. In this paper, multi-scale fractal dimension concept was used to extract a set of textural features in order to perform texture analysis for breast tissues samples. The box counting method was used to estimate the multi fractal dimensions. A feed forward neural network was used to classify different types of breast tissues according to the extracted fractal dimension vectors. For ANN training purpose the back-propagation training algorithm was used. Evaluation tests were carried on 368 breast tissues images. The test results indicated that the best attained success rate was around 97%.

Published in:

Soft Computing and Pattern Recognition (SoCPaR), 2011 International Conference of

Date of Conference:

14-16 Oct. 2011

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