Tissue segmentation in ultrasound images by using genetic algorithms

Dokur Z., Ölmez T.

EXPERT SYSTEMS WITH APPLICATIONS, vol.34, no.4, pp.2739-2746, 2008 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 34 Issue: 4
  • Publication Date: 2008
  • Doi Number: 10.1016/j.eswa.2007.05.002
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.2739-2746
  • Istanbul Technical University Affiliated: Yes


This paper presents a genetic based incremental neural network (GINeN) for the segmentation of tissues in ultrasound images. Performances of the GINeN and the Kohonen network are investigated for tissue segmentation in ultrasound images. Feature extraction is carried out by using continuous wavelet transform. Pixel intensities at the same spatial location on 12 wavelet planes and on the original image are considered as features, leading to 13-dimensional feature vectors. The same training set is used for the training of the Kohonen network and the GINeN.