Abstract
In this paper the novel neural NARX technique was applied for classification and detection purposes. Decision making was performed in two stages: feature extraction using the principal component analysis (PCA) and the neural NARX model trained with the backpropagation method. The performance of the neural NARX-based classifier was evaluated in terms of training and classification accuracies. The results confirmed that the proposed neural NARX-based classifier has potential in detecting the tumors.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 IFMBE
About this paper
Cite this paper
Anh, H.P.H., Loi, L.T. (2013). Medical Image Classification and Symptoms Detection Using Fuzzy NARX Technique. In: Toi, V., Toan, N., Dang Khoa, T., Lien Phuong, T. (eds) 4th International Conference on Biomedical Engineering in Vietnam. IFMBE Proceedings, vol 49. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32183-2_83
Download citation
DOI: https://doi.org/10.1007/978-3-642-32183-2_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32182-5
Online ISBN: 978-3-642-32183-2
eBook Packages: EngineeringEngineering (R0)