Andreas Schreiber

Andreas Schreiber

We want to analyze visually, to what extend team members and external developers contribute to open-source projects. This gives a high-level impression about collaboration in that projects. We achieve this by recording provenance of the development process and use graph drawing on the resulting provenance graph. Our graph drawings show, which developers are jointly changed the same files -- and to what extent -- which we show at Germany's COVID-19 exposure notification app 'Corona-Warn-App'.

Brigitte Boden, Jan Flink, Niklas Först et al.

We present RCE (Remote Component Environment), an open-source framework developed primarily at DLR (German Aerospace Center) that enables its users to construct and execute multidisciplinary engineering workflows comprising multiple disciplinary tools. To this end, RCE supplies users with an easy-to-use graphical interface that allows for the intuitive integration of disciplinary tools. Users can execute the individual tools on arbitrary nodes present in the network and all data accrued during the execution of the workflow are collected and stored centrally. Hence, RCE makes it easy for collaborating engineers to contribute their individual disciplinary tools to a multidisciplinary design or analysis, and simplifies the subsequent analysis of the workflow's results.

Aurélie Breidenbach, Caroline Mahlow, Andreas Schreiber

Gender diversity in the tech sector is - not yet? - sufficient to create a balanced ratio of men and women. For many women, access to computer science is hampered by socialization-related, social, cultural and structural obstacles. The so-called implicit gender bias has a great influence in this respect. The lack of contact in areas of computer science makes it difficult to develop or expand potential interests. Female role models as well as more transparency of the job description should help women to promote their - possible - interest in the job description. However, gender diversity can also be promoted and fostered through adapted measures by leaders.

Anneke Meyer, Grzegorz Chlebus, Marko Rak et al.

Background and Objective: Accurate and reliable segmentation of the prostate gland in MR images can support the clinical assessment of prostate cancer, as well as the planning and monitoring of focal and loco-regional therapeutic interventions. Despite the availability of multi-planar MR scans due to standardized protocols, the majority of segmentation approaches presented in the literature consider the axial scans only. Methods: We propose an anisotropic 3D multi-stream CNN architecture, which processes additional scan directions to produce a higher-resolution isotropic prostate segmentation. We investigate two variants of our architecture, which work on two (dual-plane) and three (triple-plane) image orientations, respectively. We compare them with the standard baseline (single-plane) used in literature, i.e., plain axial segmentation. To realize a fair comparison, we employ a hyperparameter optimization strategy to select optimal configurations for the individual approaches. Results: Training and evaluation on two datasets spanning multiple sites obtain statistical significant improvement over the plain axial segmentation ($p<0.05$ on the Dice similarity coefficient). The improvement can be observed especially at the base ($0.898$ single-plane vs. $0.906$ triple-plane) and apex ($0.888$ single-plane vs. $0.901$ dual-plane). Conclusion: This study indicates that models employing two or three scan directions are superior to plain axial segmentation. The knowledge of precise boundaries of the prostate is crucial for the conservation of risk structures. Thus, the proposed models have the potential to improve the outcome of prostate cancer diagnosis and therapies.