DWT to Classify Automatically the Placental Tissues Development: Neural Network Approach
Mohammad Ayache, Mohamad Khalil & Francois Tranquart
Journal of Computer Science, Volume 6, Issue 6, pp. 634–640 · doi.org/10.3844/jcssp.2010.634.640
Abstract
Problem statement: This study proposed an approach for classification of placental tissues development using ultrasound images. Approach: This approach was based to the selection of tissues, feature extraction by discrete wavelet transform and classification by neural network and especially the Multi Layer Perceptron (MLP). Results: The proposed approach was tested for ultrasound placental images; resulting in 95% success rate. Conclusion/Recommendations: The method showed a good recognition for placental tissues and will be useful for detection of the placental anomalies those concerning the premature birth and the intrauterine growth retardation.
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Ayache, M., Khalil, M. & Tranquart, F. (2010). DWT to Classify Automatically the Placental Tissues Development: Neural Network Approach. Journal of Computer Science, 6(6), 634–640. https://doi.org/10.3844/jcssp.2010.634.640
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