Paper
23 February 2012 CT performance as a variable function of resolution, noise, and task property for iterative reconstructions
Baiyu Chen, Samuel Richard, Olav Christianson, Xiaodong Zhou, Ehsan Samei
Author Affiliations +
Abstract
The increasing availability of iterative reconstruction (IR) algorithms on clinical scanners is creating a demand for effectively and efficiently evaluating imaging performance and potential dose reduction. In this study, the location- and task-specific evaluation was performed using detectability index (d') by combining a task function, the task transfer function (TTF), and the noise power spectrum (NPS). Task function modeled a wide variety detection tasks in terms of shape and contrast. The TTF and NPS were measured from a physical phantom as a function of contrast and dose levels. Measured d' values were compared between three IRs (IRIS, SAFIRE3 and SAFIRE5) and conventional filtered back-projection (FBP) at various dose levels, showing an equivalent performance of IR at lower dose levels. AUC further calculated from d' showed that compared to FBP, SAFIRE5 may reduce dose by up to 50-60%; SAFIRE3 and IRIS by up to 20-30%. This study provides an initial framework for the localized and task-specific evaluation of IRs in CT and a guideline for the identification of optimal operating dose point with iterative reconstructions.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Baiyu Chen, Samuel Richard, Olav Christianson, Xiaodong Zhou, and Ehsan Samei "CT performance as a variable function of resolution, noise, and task property for iterative reconstructions", Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83131K (23 February 2012); https://doi.org/10.1117/12.913220
Lens.org Logo
CITATIONS
Cited by 11 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Reconstruction algorithms

Infrared imaging

IRIS Consortium

Eye models

Optical filters

Scanners

Image quality

Back to Top