Three-dimensional image segmentation using neural networks

Jin-Shin Chou; Chin-Tu Chen; Wei-Chung Lin

doi:10.1117/12.148669

29 July 1993 Three-dimensional image segmentation using neural networks

Jin-Shin Chou, Chin-Tu Chen, Wei-Chung Lin

Author Affiliations +

Proceedings Volume 1905, Biomedical Image Processing and Biomedical Visualization; (1993) https://doi.org/10.1117/12.148669
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States

Abstract

We have integrated a neural network model. Kohonen's self-organizing feature maps, with the idea of fuzzy sets and applied this model to the problem of 3-D image segmentation. In the proposed method, a Kohonen network provides the basic structure and update rule, whereas fuzzy membership values control the learning rate. The calculation of learning rate is based on a fuzzy clustering algorithm. The experimental results show that the speed of convergence is fast. The major strength of the proposed approach is its unsupervised nature. Moreover, the computer memory requirement is smaller and the computation time is less than that of a conventional 3-D region-based method.

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Jin-Shin Chou, Chin-Tu Chen, and Wei-Chung Lin "Three-dimensional image segmentation using neural networks", Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); https://doi.org/10.1117/12.148669

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