Local response prediction in model-based CT material decomposition

Wenying Wang, Steven Tilley, Matthew Tivnan, J. Webster Stayman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Spectral CT is an emerging modality that permits material decomposition and density estimation through the use of energy-dependent information in measurements. Direct model-based material decomposition algorithms have been developed that incorporate statistical models and advanced regularization schemes to improve density estimates and lower exposure requirements. However, understanding and control of the relationship between regularization and image properties is complex with interactions between spectral channels and material bases. In particular, regularization in one material basis can affect the image properties of other material bases, and vice versa. In this work, we derived a closed-form set of local impulse responses for the solutions to a general, regularized, model-based material decomposition (MBMD) objective. These predictors quantify both the spatial resolution in each material image as well as the influence of regularization of one material basis on other material images. This information can be used prospectively to tune regularization parameters for specific imaging goals.

Original languageEnglish (US)
Title of host publication15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
EditorsSamuel Matej, Scott D. Metzler
PublisherSPIE
ISBN (Electronic)9781510628373
DOIs
StatePublished - Jan 1 2019
Event15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019 - Philadelphia, United States
Duration: Jun 2 2019Jun 6 2019

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11072
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019
CountryUnited States
CityPhiladelphia
Period6/2/196/6/19

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Local response prediction in model-based CT material decomposition'. Together they form a unique fingerprint.

  • Cite this

    Wang, W., Tilley, S., Tivnan, M., & Stayman, J. W. (2019). Local response prediction in model-based CT material decomposition. In S. Matej, & S. D. Metzler (Eds.), 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine [110720Z] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11072). SPIE. https://doi.org/10.1117/12.2534437