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For complex segmentation tasks, the achievable accuracy of fully automatedsystems is inherently limited. Specifically, when a precise segmentation resultis desired for a small amount of given data sets, semi-automatic methodsexhibit a clear benefit for the user. The optimization of human computerinteraction (HCI) is an essential part of interactive image segmentation.Nevertheless, publications introducing novel interactive segmentation systems(ISS) often lack an objective comparison of HCI aspects. It is demonstrated,that even when the underlying segmentation algorithm is the same throughoutinteractive prototypes, their user experience may vary substantially. As aresult, users prefer simple interfaces as well as a considerable degree offreedom to control each iterative step of the segmentation. In this article, anobjective method for the comparison of ISS is proposed, based on extensive userstudies. A summative qualitative content analysis is conducted via abstractionof visual and verbal feedback given by the participants. A direct assessment ofthe segmentation system is executed by the users via the system usability scale(SUS) and AttrakDiff-2 questionnaires. Furthermore, an approximation of thefindings regarding usability aspects in those studies is introduced, conductedsolely from the system-measurable user actions during their usage ofinteractive segmentation prototypes. The prediction of all questionnaireresults has an average relative error of 8.9%, which is close to the expectedprecision of the questionnaire results themselves. This automated evaluationscheme may significantly reduce the resources necessary to investigate eachvariation of a prototype's user interface (UI) features and segmentationmethodologies.

A Semi-Automated Usability Evaluation Framework for Interactive Image Segmentation Systems