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Published in: Journal of Digital Imaging 4/2004

01-12-2004

Novel Genetic-Neuro-Fuzzy Filter for Speckle Reduction from Sonography Images

Authors: Ali Rafiee, PhD, Mohammad Hasan Moradi, Assistant Professor, Mohammad Reza Farzaneh, Assistant Professor

Published in: Journal of Imaging Informatics in Medicine | Issue 4/2004

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Abstract

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.
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Metadata
Title
Novel Genetic-Neuro-Fuzzy Filter for Speckle Reduction from Sonography Images
Authors
Ali Rafiee, PhD
Mohammad Hasan Moradi, Assistant Professor
Mohammad Reza Farzaneh, Assistant Professor
Publication date
01-12-2004
Publisher
Springer-Verlag
Published in
Journal of Imaging Informatics in Medicine / Issue 4/2004
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-004-1026-2

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