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Unsupervised segmentation of multi-echo MR images with an ART-based neural network

Conference Paper


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 a 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.

Publication Date


  • 1995

Citation


  • Li, W., & Attikiouzel, Y. (1995). Unsupervised segmentation of multi-echo MR images with an ART-based neural network. In IEEE International Conference on Neural Networks - Conference Proceedings Vol. 5 (pp. 2600-2604).

Scopus Eid


  • 2-s2.0-0029457526

Start Page


  • 2600

End Page


  • 2604

Volume


  • 5

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 a 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.

Publication Date


  • 1995

Citation


  • Li, W., & Attikiouzel, Y. (1995). Unsupervised segmentation of multi-echo MR images with an ART-based neural network. In IEEE International Conference on Neural Networks - Conference Proceedings Vol. 5 (pp. 2600-2604).

Scopus Eid


  • 2-s2.0-0029457526

Start Page


  • 2600

End Page


  • 2604

Volume


  • 5