We have extended a classical quality control (QC) algorithm by integrating a deep learning neural network, resulting in SalaciaML-2-Arctic , a tool for automated QC of Arctic Ocean temperature and salinity profile data. The neural network component was trained on the Unified Database for Arctic and Subarctic Hydrography (UDASH), which has been quality-controlled and labeled by expert oceanographers. SalaciaML-2-Arctic successf...

Purpose For the status evaluation of intracranial aneurysms (IAs), morphological and hemodynamic parameters can provide valuable information. For their extraction, a separation of the aneurysm sac from its parent vessel is required that yields the neck curve and the ostium. However, manual and subjective neck curve and ostium definitions might lead to inaccurate IA assessments. Methods The research project VICTORIA was initiat...

Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Ame...