Title :
Segmentation of ultrasound images by using quantizer neural network
Author :
Dokur, Zümray ; Kurnaz, Mehmet Nadir ; Ölmez, Tamer
Author_Institution :
Dept. of Electron. & Commun. Eng., Istanbul Tech. Univ., Turkey
Abstract :
A quantizer neural network (QNN) is proposed for the segmentation of ultrasound images. The elements of the feature vectors are formed by the image intensities within the neighborhood of the pixel of interest. The QNN is a hybrid neural network structure, which is trained by genetic algorithms. The genetic algorithms are used to find optimum values for the weights of the nodes. The hybrid neural network is compared with a multilayer perceptron (MLP) for the segmentation of ultrasound images.
Keywords :
genetic algorithms; image segmentation; learning (artificial intelligence); neural nets; ultrasonic imaging; US image segmentation; genetic algorithms; hybrid neural network structure; image intensities; multilayer perceptron; neural net training; node weight optimum values; quantizer neural network; the feature vectors; Artificial neural networks; Biomedical imaging; Electronic mail; Genetic algorithms; Image segmentation; Multi-layer neural network; Multilayer perceptrons; Neural networks; Pixel; Ultrasonic imaging;
Conference_Titel :
Computer-Based Medical Systems, 2002. (CBMS 2002). Proceedings of the 15th IEEE Symposium on
Print_ISBN :
0-7695-1614-9
DOI :
10.1109/CBMS.2002.1011386
