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Segmentation of ultrasound images by using an incremental self-organized map

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3 Author(s)
Kurnaz, M.N. ; Dept. of Electron. & Commun., Istanbul Tech. Univ., Turkey ; Dokur, Z. ; Olmez, T.

A new incremental self-organized map is proposed for the segmentation of the ultrasound images. Elements of the feature vectors are formed by the fast Fourier transform (FFT) of image intensities in 4×4 square blocks. In this study, two neural networks for segmentation are comparatively examined: Kohonen map, and incremental self-organized map (ISOM). It is observed that ISOM gives the best classification performance with less number of nodes after a short training time.

Published in:

Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE  (Volume:3 )

Date of Conference:

2001