Towards a Catalog of Usability Smells

This paper presents a catalog of smells in the context of interactive applications. These so-called usability smells are indicators of poor design on an application’s user interface, with the potential to hinder not only its usability but also its maintenance and evolution. To eliminate such usability smells we discuss a set of program/usability refactorings. In order to validate the presented usability smells catalog, and the associated refactorings, we present a preliminary empirical study with software developers in the context of a real open source hospital management application. Moreover, a tool that computes graphical user interface behavior models, giving the applications’ source code, is used to automatically detect usability smells at the model level.

Semi-automatic 3D Segmentation Of Costal Cartilage In CT Data From Pectus Excavatum Patients

One of the current frontiers in the clinical management of Pectus Excavatum (PE) patients is the prediction of the surgical outcome prior to the intervention. This can be done through computerized simulation of the Nuss procedure, which requires an anatomically correct representation of the costal cartilage. To this end, we take advantage of the costal cartilage tubular structure to detect it through multi-scale vesselness filtering. This information is then used in an interactive 2D initialization procedure which uses anatomical maximum intensity projections of 3D vesselness feature images to efficiently initialize the 3D segmentation process. We identify the cartilage tissue centerlines in these projected 2D images using a livewire approach. We finally refine the 3D cartilage surface through region-based sparse field level-sets. We have tested the proposed algorithm in 6 noncontrast CT datasets from PE patients. A good segmentation performance was found against reference manual contouring, with an average Dice coefficient of 0.75±0.04 and an average mean surface distance of 1.69±0.30mm. The proposed method requires roughly 1 minute for the interactive initialization step, which can positively contribute to an extended use of this tool in clinical practice, since current manual delineation of the costal cartilage can take up to an hour.