@inproceedings{2125e2418cc84052bd3edea6894a6bf2,
title = "Model-based material decomposition with system blur modeling",
abstract = "In this work, we present a novel model-based material decomposition (MBMD) approach for x-ray CT that includes system blur in the measurement model. Such processing has the potential to extend spatial resolution in material density estimates - particularly in systems where different spectral channels exhibit different spatial resolutions. We illustrate this new approach for a dual-layer detector x-ray CT and compare MBMD algorithms with and without blur in the reconstruction forward model. Both qualitative and quantitative comparisons of performance with and without blur modeling are reported. We find that blur modeling yields images with better recovery of high-resolution structures in an investigation of reconstructed line pairs as well as lower cross-talk bias between material bases that is ordinarily found due to mismatches in spatial resolution between spectral channels. The extended spatial resolution of the material decompositions has potential application in a range of high-resolution clinical tasks and spectral CT systems where spectral channels exhibit different spatial resolutions.",
author = "Wenying Wang and Matthew Tivnan and Gang, {Grace J.} and Yiqun Ma and Qian Cao and Minghui Lu and Josh Star-Lack and Colbeth, {Richard E.} and Wojciech Zbijewski and Stayman, {J. Webster}",
note = "Publisher Copyright: {\textcopyright} 2020 SPIE.; Medical Imaging 2020: Physics of Medical Imaging ; Conference date: 16-02-2020 Through 19-02-2020",
year = "2020",
doi = "10.1117/12.2549549",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Guang-Hong Chen and Hilde Bosmans",
booktitle = "Medical Imaging 2020",
}