Abstract
Spiking Neuron Networks (SNNs) overcome the computational power of neural networks made of thresholds or sigmoidal units. Indeed, SNNs add a new dimension, the temporal axis, to the representation capacity and the processing abilities of neural networks. In this paper, we present how SNN can be applied with efficacy for cell microscopic image segmentation. Results obtained confirm the validity of the approach. The strategy is performed on cytological color images. Quantitative measures are used to evaluate the resulting segmentations. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Meftah, B., Lezoray, O., Lecluse, M., & Benyettou, A. (2010). Cell microscopic segmentation with spiking neuron networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6352 LNCS, pp. 117–126). https://doi.org/10.1007/978-3-642-15819-3_16
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