About QAF
A web-based platform for image quality assessment and quality control in photon-counting and multi-energy CT — from per-energy-bin measurement to scheduled, recorded QC programmes. Developed at Khalifa University of Science and Technology.
What is QAF?
QAF (Quality Assessment Framework) is a web-based platform for evaluating image quality in photon-counting detector (PCD) and multi-energy computed tomography. Everything runs in the browser — upload a phantom study, draw regions of interest, and obtain quantitative results without installing software or writing code.
Unlike conventional CT tools, QAF analyses every energy bin separately. Image uniformity, artefacts, noise and resolution are measured per bin, alongside spectral and material analysis that only multi-energy CT makes possible — material identification and quantification, electron density and effective atomic number. Every result can be judged against acceptance criteria, exported, and stored permanently against a specific scanner.
Our Mission.
Photon-counting CT is advancing faster than the quality control practice around it. Published guidance covers conventional and vendor-processed images, but leaves energy-bin data largely unaddressed — so laboratories are left assembling their own scripts, with results that are difficult to reproduce or compare between sites.
QAF exists to close that gap: to make multi-energy image quality assessment standardised, reproducible and transparent. Analysis methods follow published protocols and are verified against known references; measurements are recorded with the criteria applied, the operator and the date; and scheduling, baselines and trending turn one-off measurements into a quality control programme that can demonstrate how a scanner has performed over time.
Our Team.
The people behind QAF at Khalifa University
Get in Touch.
Have questions about QAF, need help with an analysis, or interested in collaborating? Use the address that best matches your enquiry — technical problems and account issues go to support, questions about the platform and its methodology to the QAF team, and research collaboration or academic enquiries directly to the Principal Investigator. We are based at Khalifa University of Science and Technology in Abu Dhabi, UAE.