Over the past years, the topic of quality assurance (QA) has been a steady companion and although I might not necessarily like QA on f, there’s no doubt that thinking of negatively influencing variables of a working process is strengthening the awareness of potential issues and therefore still earns a +1 on g. Developing and implementing standard operating procedures (SOP) is then the next step after the detailed risk assessment of a process and aims to standardize the findings of the expert, who is aware of all influencing variables and context-specific dependencies. And by fixing this approach into a written SOP, it can be ensured that the results obtained by following this procedure are consistent and don’t require the expert’s knowledge. Despite this rather short and simplified description of QA, it is probably common-sense that the benefit of eliminating (or at least consistently managing) critical issues of the process generally increases the quality of the results.
The theoretical basis of Computed Tomography (CT) finds its origins in 1917, when the Austrian mathematician Johan Radon (16 December 1887 – 25 May 1956) proved that an n-dimensional object can be reconstructed from its (n-1)-dimensional projections . However, only in the second half of the century the mathematical basis for the actual CT image reconstruction was presented in two papers by Allan M. Cormack (Feb. 23, 1924 – May 7, 1998) [2, 3] in 1964 and 1965, respectively.