README.md

Tensor-valued diffusion encoding for diffusional variance decomposition (DIVIDE): Technical feasibility in clinical MRI systems

Filip Szczepankiewicz 1*, Jens Sjölund 2,3,4, Freddy Ståhlberg 1,5, Jimmy Lätt 6, Markus Nilsson 5,7

1. Lund University, Department of Clinical Sciences Lund, Medical Radiation Physics, Lund, Sweden
2. Elekta Instrument AB, Kungstensgatan 18, Box 7593, SE-103 93, Stockholm, Sweden
3. Linköping University, Department of Biomedical Engineering, Linköping, Sweden
4. Linköping University, Center for Medical Image Science and Visualization (CMIV), Linköping, Sweden
5. Lund University, Department of Clinical Sciences Lund, Diagnostic Radiology, Lund, Sweden
6. Skåne University Hospital, Department of Imaging and Function, Lund, Sweden
7. Lund University, Lund University Bioimaging Center, Lund, Sweden

*Corresponding author
E-mail: filip.szczepankiewicz@med.lu.se

Reference

If you use these resources, please cite:
Szczepankiewicz F, Sjölund J, Ståhlberg F, Lätt J, Nilsson M. Tensor-valued diffusion encoding for diffusional variance decomposition (DIVIDE): Technical feasibility in clinical MRI systems. PLoS ONE. 2019;14(3):e0214238. https://doi.org/10.1371/journal.pone.0214238

Related resources can be found at the FWF sequence GIT repository