evaluating data sets for training and testing. Similarity measures between segmentation outcome and ground truth images are utilized to quantify the quality of the segmentation result.

With (), a complete ground truth data set would also consist of the adaptive user interactions which advance the segmentation process. Therefore, when comparing , the user needs to be involved in the evaluation process. User interaction data however is highly dependent on (1) the users’ domain knowledge and the unique learning effect of the human throughout a period of exposure to the problem domain, (2) the system’s underlying segmentation method and the users’ preferences toward this technique, as well as (3) the design and usability (the user experience [@hassenzahl2006user; @law2009understanding]) of the interface which is presented to the user during the interactive segmentation procedure [@caro1979inter; @hong2014interobserver]. This includes users’ differing preferences towards diverse interaction systems and tolerances for unexpected system behavior. Considering , an analytically expressed objective function for an interactive system is hard to define. Intuitively, the user wants to achieve a satisfying result in a short amount of time with ease [@kohli2012user]. A direct assessment of a system’s usability is enabled via standardized questionnaires, as described in **Sec.**\[sec:questionnaires\]. Individual usage of 