Automating adaptive image generation for medical devices using aspect-oriented programming

Image generation, e.g., in computer tomographs, requires the use of sophisticated algorithms which are characterized (i) by a large variability to enable generation of different types of images and (ii) a strong need for dynamic reconfiguration to adapt image generation, e.g., to individual patients. On the application level, such characteristics are frequently scattered all over the code of the application. This suggests the use of aspect-oriented programming (AOP) techniques to modularize such crosscutting functionality. In this paper we present an approach to automate image generation tasks using AOP and their application in the context of medical devices from Siemens AG, Germany. Concretely, we present three results: (i) a motivation why imaging software can benefit from dynamic AOP, (ii) a case study of how image generation, in particular for medical devices, can be adapted using the Arachne system for dynamic AOP in C, and (iii) a suitable aspect language and its realization within Arachne.