Mondal, Partha P and Rajan, K (2004) Iterative Image Reconstruction for Emission Tomography Using Fuzzy Potential. In: 2004 IEEE Nuclear Science Symposium Conference Record, 16-22 October, Roma, Italy, Vol.6, 3616-3619.
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Abstract
The maximum a-posteriori (MAP) and maximum likelihood (ML) algorithm produces good reconstruction for emission tomography. However they still suffer from noise and optimal smoothing. Penalized iterative algorithms based on MAP-estimation often result in over smooth reconstructions. These algorithms fail to determine the density class in the reconstructed image and hence penalize the pixels irrespective of the density class. Reconstruction with better edge information is often difficult due to the lack of prior knowledge. In this paper, a fuzzy logic based approach is proposed to model the nature of pixel-pixel interaction. The proposed algorithm consists of two elementary steps: (1) Edge detection - fuzzy rule based derivatives are used for the detection of edges in the nearest neighborhood window. (2) Fuzzy smoothing - penalization is performed only for those pixels for which no edge is detected in the nearest neighborhood. Both of these operations are carried out iteratively until convergence. Quantitative analysis shows that the proposed fuzzy rule based reconstruction algorithm is capable of producing better reconstructed images when compared with MAP and MRP reconstructed images.
Item Type: | Conference Paper |
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Publisher: | IEEE |
Additional Information: | �©1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Department/Centre: | Division of Physical & Mathematical Sciences > Physics |
Date Deposited: | 01 Dec 2005 |
Last Modified: | 19 Sep 2010 04:21 |
URI: | http://eprints.iisc.ac.in/id/eprint/4238 |
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