Conveners
Use case 1: pseudonymised T1 magnetic resonance images segmentation
- Philip Langer (UMG)
Description
The department of diagnostic and interventional neuroradiology at the university medical center Göttingen is working on an approach to utilize the GWDG Secure Workflow to externally segment pseudonymised T1 magnetic resonance images. The pipeline aims to generate reliable, reproducible and precise volumetric information on atrophy patterns within a patients brain, while running parallel to the clinical workflow of a regular MRI-scan. The goal is to provide the physician in a timely manner with quantified hints to simplify the search for the correct diagnosis right after the MRI-scan finished.
The used FastSurfer neural net was trained on unedited MRI-images, and thus almost any alteration of the actual imaging data (f.e. removal of facial features) to ensure maximum protection of patient data leads to inaccurate and unusable segmentation results, making the utilization of externally provided hardware a difficult venture.
The need for best possible data protection and the additional requirement of powerful hardware to meet the temporal criteria are a well fitting use case for the Secure Workflow on GWDGs HPC-Cluster.
