Research Article Open Access

DWT to Classify Automatically the Placental Tissues Development: Neural Network Approach

Mohammad Ayache, Mohamad Khalil and Francois Tranquart

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.

Journal of Computer Science
Volume 6 No. 6, 2010, 634-640

DOI: https://doi.org/10.3844/jcssp.2010.634.640

Submitted On: 29 January 2010 Published On: 30 June 2010

How to Cite: 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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Keywords

  • Placenta
  • wavelet transform
  • neural networks
  • MLP