Brain imaging classification based on Learning Vector Quantization

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

The performance accuracy of the Artificial Neural Network (ANN) is highly dependent on the class distribution. Data multi-randomization before classification is proposed in this paper in order to obtain a proper classification model, which guaranties well performance of the classifiers. Multi randomization aims to allocate the best class distribution by re-ordering the input dataset randomly. In this paper, Learning Vector Quantization (LVQ) which is a supervised ANN, Multilayer perceptron (MLP), unsupervised Self organizing Map (SOM) and Radial Base Function (RBF) are used to classify multi randomized brain Magnetic Resonance Imaging (MRI) dataset. The proposed method showed significant improvement in the stability of the classifiers.

Original languageEnglish
Title of host publication2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013
DOIs
Publication statusPublished - 2013
Event2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013 - Sharjah
Duration: 12 Feb 201314 Feb 2013

Other

Other2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013
CitySharjah
Period12/2/1314/2/13

Fingerprint

Vector quantization
Brain
Classifiers
Neural networks
Imaging techniques
Self organizing maps
Multilayer neural networks
Magnetic Resonance Imaging

Keywords

  • Artificial Neural Network
  • data multi-resampling
  • Learning Vector Quantization
  • Magnetic Resonance Imaging

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

Cite this

Nayef, B. H., Sahran, S., Iqbal Hussain, R., & Sheikh Abdullah, S. N. H. (2013). Brain imaging classification based on Learning Vector Quantization. In 2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013 [6487253] https://doi.org/10.1109/ICCSPA.2013.6487253

Brain imaging classification based on Learning Vector Quantization. / Nayef, Baher H.; Sahran, Shahnorbanun; Iqbal Hussain, Rizuana; Sheikh Abdullah, Siti Norul Huda.

2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013. 2013. 6487253.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nayef, BH, Sahran, S, Iqbal Hussain, R & Sheikh Abdullah, SNH 2013, Brain imaging classification based on Learning Vector Quantization. in 2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013., 6487253, 2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013, Sharjah, 12/2/13. https://doi.org/10.1109/ICCSPA.2013.6487253
Nayef BH, Sahran S, Iqbal Hussain R, Sheikh Abdullah SNH. Brain imaging classification based on Learning Vector Quantization. In 2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013. 2013. 6487253 https://doi.org/10.1109/ICCSPA.2013.6487253
Nayef, Baher H. ; Sahran, Shahnorbanun ; Iqbal Hussain, Rizuana ; Sheikh Abdullah, Siti Norul Huda. / Brain imaging classification based on Learning Vector Quantization. 2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013. 2013.
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