Image quality assessment is performed during routine quality assurance testing (QA) of fluoroscopy units at University Hospital Southampton NHS Foundation Trust. These image quality assessments are performed ‘live’ and in a qualitative manner, using standard methods following relevant IPEM guidance. However, the results of such live qualitative tests are prone to observer bias, reducing their reliability. This report describes a proof-of-concept QA system for automated quantitative image quality assessment of fluoroscopy images. Analysis code has been written in the ImageJ macro language to quantitatively analyse fluoroscopy images of the Leeds Test Objects TOR 18FG test object without user intervention. Measurements performed include contrast-to-noise (CNR) measurements and the number of ‘detectable’ low contrast discs. DICOM server-side scripting is utilised to run the analysis code automatically on receipt of the DICOM images. Results obtained using this QA system are compared to current QA methods. The QA system has been designed so that it could be adapted in the future to perform other image quality QA tests, including for other imaging modalities.