Interval-based reconstruction for uncertainty quantification in PET

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.
Document type :
Journal articles
Complete list of metadatas

Cited literature [33 references]  Display  Hide  Download
Contributor : Olivier Strauss <>
Submitted on : Monday, February 12, 2018 - 4:24:34 PM
Last modification on : Thursday, January 9, 2020 - 10:48:01 AM
Long-term archiving on: Monday, May 7, 2018 - 4:52:56 PM



Florentin Kucharczak, Kevin Loquin, Irène Buvat, Olivier Strauss, Denis Mariano-Goulart. Interval-based reconstruction for uncertainty quantification in PET. Physics in Medicine and Biology, IOP Publishing, 2018, 63 (3), ⟨10.1088/1361-6560/aa9ea6⟩. ⟨lirmm-01707254⟩



Record views


Files downloads