Fuzzy-rule-based image reconstruction for positron emission tomography.

Partha P Mondal; K Rajan

doi:10.1364/josaa.22.001763

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Fuzzy-rule-based image reconstruction for positron emission tomography.

Partha P Mondal·K Rajan

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Abstract

Positron emission tomography (PET) and single-photon emission computed tomography have revolutionized the field of medicine and biology. Penalized iterative algorithms based on maximum a posteriori (MAP) estimation eliminate noisy artifacts by utilizing available prior information in the reconstruction process but often result in a blurring effect. MAP-based 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 because prior knowledge is not taken into account. The recently introduced median-root-prior (MRP)-based algorithm preserves the edges, but a steplike streaking effect is observed in the reconstructed image, which is undesirable. A fuzzy approach is proposed for modeling the nature of interpixel interaction in order to build an artifact-free edge-preserving reconstruction. The proposed algorithm consists of two elementary steps: (1) edge detection, in which fuzzy-rule-based derivatives are used for the detection of edges in the nearest neighborhood window (which is equivalent to recognizing nearby density classes), and (2) fuzzy smoothing, in which 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 the image converges. Analysis shows that the proposed fuzzy-rule-based reconstruction algorithm is capable of producing qualitatively better reconstructed images than those reconstructed by MAP and MR P algorithms. The reconstructed images a resharper, with small features being better resolved owing to the nature of the fuzzy potential function.

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Algorithms Artificial Intelligence Brain Fuzzy Logic Humans Image Enhancement Image Interpretation, Computer-Assisted Phantoms, Imaging Positron-Emission Tomography Reproducibility of Results Sensitivity and Specificity Evaluation Study Journal Article Research Support, Non-U.S. Gov't

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Partha P Mondal, K Rajan. 2005. Fuzzy-rule-based image reconstruction for positron emission tomography.. https://doi.org/10.1364/josaa.22.001763

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