2020/10/03 by Matthew Tivnan, Wenying Wang, Tivnan, Matthew +3
Computer Science · Engineering · Medicine · #Advanced X-ray and CT Imaging #FOS: Physical sciences #Medical Image Segmentation Techniques #Medical Imaging Techniques and Applications #Medical Physics (physics.med-ph)
paper · pdf · doi:10.48550/arxiv.2010.01371
openalex publication_date 2020/10/03 · openalex created_date 2020/10/08 · openalex updated_date 2026/07/28
Model-based material decomposition is a statisticaliterative reconstruction framework where basis material densityimages are estimated directly from spectral CT data. This methoduses a physical model for polyenergetic x-ray transmission andattenuation and therefore it does not typically suffer frombeam-hardening artifacts. However, this estimation is a poorly-conditioned inverse problem due to the strong anticorrelationbetween basis materials. In this work we propose an precondi-tioned optimization algorithm for a nonlinear penalized weightedleast-squares objective function.