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Unsupervised 3-D restoration of tomographic images by constrained Wiener filtering

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2 Author(s)
Pereiro, S. ; Biomed. Eng. Inst., Ecole Polytech. de Montreal, Que., Canada ; Goussard, Y.

This communication presents a non-supervised restoration method based on a constrained Wiener filter. We implement our filter in the spatial domain and perform the filtering in 3-D. Our central contribution lies in the derivation of a cross validation based algorithm which estimates the noise variance from the observed image. Exploitation of the partitioned matrix inversion lemma leads to a reasonable computation time. Results indicate that the method is able to determine the noise variance with an accuracy sufficient to produce acceptable results in the restoration at low signal-to-noise ratios. However at higher signal-to-noise ratios (above 15 dB) some undersmoothing is observed

Published in:

Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE  (Volume:2 )

Date of Conference:

30 Oct-2 Nov 1997