Automated data pipeline for clinical quantitative7T MR

Project: Other

Description

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
AcronymMIPP
StatusActive
Effective start/end date2018/01/08 → …

Collaborative partners

Participants

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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