Three-dimensional image segmentation using neural networks

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.