Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction.

Journal: Medical physics
Published Date: Oct 1, 2015

Abstract

PURPOSE: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging.

Authors

  • Brendan L Eck
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106.
  • Rachid Fahmi
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106.
  • Kevin M Brown
    Philips Healthcare, Cleveland, Ohio 44143.
  • Stanislav Zabic
    Philips Healthcare, Cleveland, Ohio 44143.
  • Nilgoun Raihani
    Philips Healthcare, Cleveland, Ohio 44143.
  • Jun Miao
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106.
  • David L Wilson
    Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106 and Department of Radiology, Case Western Reserve University, Cleveland, Ohio 44106.

Keywords

External Resources

Popular Topics
Recent Journals