Ultrasound Research Today is a free monthly online journal that collates and summarizes the latest research about Ultrasound, including details on screening, diagnosis, pregnancy, detection.

Novel genetic-neuro-fuzzy filter for speckle reduction from sonography images.

Rafiee A, Moradi MH, Farzaneh MR

Science and Research Campus, Islamic Azad University, Tehran, Iran. alirafiee_2000@yahoo.com

Edge-preserving speckle noise reduction is essential to computer-aided ultrasound image processing and understanding. A new class of genetic-neuro-fuzzy filter is proposed to optimize the trade-off between speckle noise removal and edge preservation. The proposed approach combines the advantages of the fuzzy, neural, and genetic paradigms. Neuro-fuzzy approaches are very promising for nonlinear filtering of noisy images. Fuzzy reasoning embedded into the network structure aims at reducing errors while fine details are being processed. The learning method based on the real-time genetic algorithms (GAs) performs an effective training of the network from a collection of training data and yields satisfactory results after a few generations.The performance of the proposed filter has been compared with that of the commonly used median and Wiener filters in reducing speckle noises on ultrasound images. We evaluate this filter by passing the filter's output to the edge detection algorithm and observing its ability to detect edge pixels.Experimental results show that the proposed genetic-neuro-fuzzy technique is very effective in speckle noise reduction as well as detail preserving even in the presence of highly noise corrupted data, and it works significantly better than other well-known conventional methods in the literature.

Published 4 February 2005 in J Digit Imaging, 17(4): 292-300.
Full-text of this article is available online (may require subscription).

© 2004-2008 Ultrasound Research Today. All Rights Reserved.