Tissue segmentation in ultrasound images by using genetic algorithms

Zümray Dokur*, Tamer Ölmez

*Bu çalışma için yazışmadan sorumlu yazar

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15 Atıf (Scopus)

Özet

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. This paper proposes the use of wavelet transform and genetic based incremental neural network together in order to increase the segmentation performance. It is observed that genetic based incremental neural network gives satisfactory segmentation performance for ultrasound images.

Orijinal dilİngilizce
Sayfa (başlangıç-bitiş)2739-2746
Sayfa sayısı8
DergiExpert Systems with Applications
Hacim34
Basın numarası4
DOI'lar
Yayın durumuYayınlandı - May 2008

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