  Segmentation is a key step in analyzing and processing medical images. Due to
the low fault tolerance in medical imaging, manual segmentation remains the de
facto standard in this domain. Besides, efforts to automate the segmentation
process often rely on large amounts of manually labeled data. While existing
software supporting manual segmentation is rich in features and delivers
accurate results, the necessary time to set it up and get comfortable using it
can pose a hurdle for the collection of large datasets. This work introduces a
client/server based online environment, referred to as Studierfenster
(studierfenster.at), that can be used to perform manual segmentations directly
in a web browser. The aim of providing this functionality in the form of a web
application is to ease the collection of ground truth segmentation datasets.
Providing a tool that is quickly accessible and usable on a broad range of
devices, offers the potential to accelerate this process. The manual
segmentation workflow of Studierfenster consists of dragging and dropping the
input file into the browser window and slice-by-slice outlining the object
under consideration. The final segmentation can then be exported as a file
storing its contours and as a binary segmentation mask. In order to evaluate
the usability of Studierfenster, a user study was performed. The user study
resulted in a mean of 6.3 out of 7.0 possible points given by users, when asked
about their overall impression of the tool. The evaluation also provides
insights into the results achievable with the tool in practice, by presenting
two ground truth segmentations performed by physicians.
