DWT to Classify Automatically the Placental Tissues Development: Neural Network Approach
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.
DOI: https://doi.org/10.3844/jcssp.2010.634.640
Copyright: © 2010 Mohammad Ayache, Mohamad Khalil and Francois Tranquart. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Placenta
- wavelet transform
- neural networks
- MLP