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

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.