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Improved automatic classification of biological particles from electron-microscopy images using genetic neural nets

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Engineering Applications of Bio-Inspired Artificial Neural Networks (IWANN 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1607))

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Abstract

In this paper several neural network classification algorithms have been applied to a real-world data case of electron microscopy data classification. Using several labeled sets as a reference, the parameters and architecture of the classifiers, LVQ (Learning Vector Quantization) trained codebooks and BP (backpropagation) trained feedforward neural-nets were optimized using a genetic algorithm. The automatic process of training and optimization is implemented using a new version of the g-lvq (genetic learning vector quantization) and G-Prop (genetic back-propagation) algorithms, and compared to a non-optimized version of the algorithms, Kohonen's LVQ and MLP trained with QuickProp. Dividing the all available samples in three sets, for training, testing and validation, the results presented here show a low average error for unknown samples. In this problem, G-Prop outperforms G-LVQ, but G-LVQ obtains codebooks with less parameters than the perceptrons obtained by G-Prop. The implication of this kind of automatic classification algorithms in the determination of three dimensional structure of biological particles is finally discused.

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Authors and Affiliations

  1. Depto. Arquitectura y Tecnología de las Computadoras, Facultad de Ciencias, GeNeura Team, Campus Fuentenueva, s/n, 18071, Granada, (Spain)

    J. J. Merelo, G. Romero & P. Castillo

  2. Departmento de Informática, Universidad de Jaén, 28040, Madrid, (Spain)

    V. Rivas

  3. Grupo de Biocomputación, CNB, 28040, Madrid, (Spain)

    A. Pascual & J. M. Carazo

Authors
  1. J. J. Merelo
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  2. V. Rivas
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  3. G. Romero
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  4. P. Castillo
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  5. A. Pascual
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  6. J. M. Carazo
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José Mira Juan V. Sánchez-Andrés

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© 1999 Springer-Verlag Berlin Heidelberg

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Merelo, J.J., Rivas, V., Romero, G., Castillo, P., Pascual, A., Carazo, J.M. (1999). Improved automatic classification of biological particles from electron-microscopy images using genetic neural nets. In: Mira, J., Sánchez-Andrés, J.V. (eds) Engineering Applications of Bio-Inspired Artificial Neural Networks. IWANN 1999. Lecture Notes in Computer Science, vol 1607. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0100504

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  • DOI: https://doi.org/10.1007/BFb0100504

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  • Print ISBN: 978-3-540-66068-2

  • Online ISBN: 978-3-540-48772-2

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