Conference paper
Unsupervised segmentation of multi-echo MR images with an ART-based neural network
Proceedings of ICNN'95 - International Conference on Neural Networks, Vol.5, pp.2600-2604
IEEE
Proceedings of the IEEE International Conference on Neural Networks (Perth, Western Australia, 27/11/1995–01/12/1995)
1995
Abstract
This paper investigates the suitability of an ART-based neural network for unsupervised segmentation of multi-echo MR images. The ART2A network was used to segment standard dual-echo MR images. Two problems were identified with the basic ART2A: one, the network was hardly convergent; and two, the categorization depended on the order of presentation of the patterns. In order to solve these two problems, a dynamic learning parameter and random pattern presentation method were introduced. Results using a number of actual dual-echo MR images with the modified ART2A network show that ART-based networks can be used for segmentation of multi-echo MR images
Details
- Title
- Unsupervised segmentation of multi-echo MR images with an ART-based neural network
- Authors/Creators
- W. Li (Author/Creator) - The University of Western AustraliaY. Attikiouzel (Author/Creator)
- Publication Details
- Proceedings of ICNN'95 - International Conference on Neural Networks, Vol.5, pp.2600-2604
- Conference
- Proceedings of the IEEE International Conference on Neural Networks (Perth, Western Australia, 27/11/1995–01/12/1995)
- Publisher
- IEEE
- Identifiers
- 991005543974507891
- Copyright
- © 1995 IEEE
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
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