AI Article Synopsis
- A new tomographic reconstruction method called non-additive interval based expectation maximization (NIBEM) is introduced, which uses intervals instead of just single values for projections.
- This method builds on the traditional maximum likelihood-expectation maximization algorithm for better estimating uncertainty in reconstructed data.
- The paper reviews existing theories about interval-based projections and showcases the NIBEM algorithm, providing examples that demonstrate its benefits and properties.
Article Abstract
A new directed interval-based tomographic reconstruction algorithm, called non-additive interval based expectation maximization (NIBEM) is presented. It uses non-additive modeling of the forward operator that provides intervals instead of single-valued projections. The detailed approach is an extension of the maximum likelihood-expectation maximization algorithm based on intervals. The main motivation for this extension is that the resulting intervals have appealing properties for estimating the statistical uncertainty associated with the reconstructed activity values. After reviewing previously published theoretical concepts related to interval-based projectors, this paper describes the NIBEM algorithm and gives examples that highlight the properties and advantages of this interval valued reconstruction.
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