In this program we research new image quality (IQ) evaluation methodologies in response to recent developments in X-ray Computed Tomography (CT) systems including iterative image reconstruction algorithms, enhancements in dual energy CT, and other nonlinear techniques. Devices based on these technologies come with claims of generating images of diagnostic value equal to or better than those obtained by conventional CT. Quantitative dose reduction claims require special testing beyond what standard CT metrics provide. We are developing physical testing methodologies, using task-based paradigms, involving the measurement of the detectability of signals at unknown location. The signal search task is clinically more realistic and more sensitive to changes in noise level and pattern. We developed phantoms for such testing and are experimentally validating and further improving the proposed procedures for 3D applications. The outcomes of this program will facilitate the interpretation of results and the comparison among devices to address specific dose reduction claims, enabling FDA to promptly address regulatory reviews of new generation imaging diagnostic devices.
Example CT image with suspicious signal locations, the true signals (marked with small circles and *), and the regions of interest randomly selected for analysis.
Current funding sources
Andreu Badal-Soler, Ph.D.
Rongping Zheng, Ph.D.
Bahaa Ghammraoui, Ph.D.
Aria Pezeshk, Ph.D.
Imaging physics laboratory
- X-ray tubes:
- Several rotating tungsten anode Varian medical X-ray tubes (RAD-70SP, G-1582BI)
- X-ray microfocus source from OXFORD Instruments designed for applications where high power, high magnification and small spot size are important.
- Digital flat-panel energy integrating detectors:
Public Domain Software
A. Wunderlich, IQmodelo: Statistical software for image quality assessment with model observers, 2014.
Selected peer-review publications
- Popescu, Nonparametric signal detectability evaluation using an exponential transformation of FROC curve, Med. Phys., 2011.
- Popescu, PET energy-based scatter estimation in the presence of randoms, and image reconstruction with energy dependent scatter and randoms corrections, IEEE Trans. Nucl. Sci., 2012.
- Popescu et al., CT image assessment by low contrast signal detectability evaluation with unknown signal location, Med. Phys., 2013.
- Vaishnav et al., Objective assessment of image quality and dose reduction in CT iterative reconstruction, Med. Phys., 2014.
- Badal et al., A real-time radiation dose monitoring system for patients and staff during interventional fluoroscopy using a GPU-accelerated Monte Carlo simulator and an automatic 3D localization system based on a depth camera, Proceedings SPIE Medical Imaging 2013: Physics of Medical Imaging, 2013.
- Rupcich et al., Reducing radiation dose to the female breast during CT coronary angiography: A simulation study comparing breast shielding, angular tube current modulation, reduced kV, and partial angle protocols using an unknown location signal-detectability metric, Medical Physics, 2013.
- Sisniega et al., Monte Carlo study of the effects of system geometry and antiscatter grids on cone-beam CT scatter distributions, Medical Physics, 2013.
- Sempau et al., A PENELOPE-based system for the automated Monte Carlo simulation of clinacs and voxelized geometries --- Application to far-from-axis fields, Medical Physics, 2011.