Applying advanced fuzzy cellular neural network AFCNN to segmentation of serial CT liver images

Abstract

In [1], a variant version of the fuzzy cellular neural network, called FCNN, is proposed to effectively segment microscopic white blood cell images. However, when applied to the segmentation of serial CT liver images, it does not work well. In this paper, FCNN is improved to be the novel neural network - Advanced Fuzzy Cellular Neural Network AFCNN. Just like FCNN, AFCNN still keeps its convergent property and global stability. When applied to segment serial CT liver images, AFCNN has the distinctive advantage over FCNN: it can keep boundary integrity better and have better recall accuracies such that the segmented images can approximate original liver images better. © Springer-Verlag Berlin Heidelberg 2005.