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Proceedings Paper

Impulse noise reduction in MR images using one rule-base merging method of fuzzy weighted mean filters
Author(s): Mohammad Sabati; Maitham Sabati; S. Abdolkarim Hosseini Ravandi; Richard Frayne
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Paper Abstract

Impulse noise contamination can affect the interpretability of the magnetic resonance (MR) images. Nonlinear adaptive techniques are often computationally expensive in reducing the noise while retaining the image details. Due to their lack of adaptability, the median filters do not always perform well when the noise probability is relatively high. To provide simplicity and adaptability, here we present a fuzzy weighted mean (FWM) filter that uses both numerical data and linguistic information. The FWM filter determines the weight for each pixel in the neighborhood in response to the local features. In this study, the training data were calculated from twenty impulse noise-free MR images obtained from different regions in humans. A 5 x 5 window was used to scan across the images. The fuzzy system was constructed using the learning from example method and was then merged with Takagi-Sugeno fuzzy system based on information obtained from experts using a one rule-base merging method. Preliminary assessment of the method on twenty noisy images showed encouraging results in effectively reducing the error in the sense of mean square (compare to median filters) and preserving edges and small structures, although the appearance of the original images was not always faithfully recovered.

Paper Details

Date Published: 15 May 2003
PDF: 11 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.480846
Show Author Affiliations
Mohammad Sabati, Seaman Family MR Research Ctr. (Canada)
Univ. of Calgary (Canada)
Maitham Sabati, Isfahan Univ. of Technology (Iran)
S. Abdolkarim Hosseini Ravandi, Isfahan Univ. of Technology (Iran)
Richard Frayne, Seaman Family MR Research Ctr. (Canada)
Univ. of Calgary (Canada)

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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