Automated data pipeline for clinical quantitative 7T MRI

Project: Other


I. dicom to nifti conversion with following functionalities:
1: retaining radiological RL-orientation
2: retaining physical signal strength (image data in [a.u.]) or quantitity (parameter maps in specified unit)
3: pseudonymization of personal data compliant with GDPR
4: creating metafiles (.json) compliant with Brain Imaging Data Structure (BIDS) standard

II. basic pre-processing

III. Access and study organization
http access
organization, pseudonynization
maintenance and storage
data sharing
Short titleMedical Imaging Processing Pipeline
Effective start/end date2018/01/08 → …

Collaborative partners

  • Lund University (lead)
  • Max Planck Institute for Human Cognitive and Brain Sciences


Related research output

Balteau, E., Tabelow, K., Ashburner, J., Callaghan, M., Draganski, B., Gunther Helms, Kherif, F., Leutritz, T., Lutti, A., Philips, C., Reimer, E., Ruthotto, L., Seif, M., Weiskopf, N., Ziegler, G. & Mohammadi, S., 2018 Jul 31, Berlin: Weierstraß Institute for Applied Analysis and Stochastics, 35 p.

Research output: Working paper

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