I have started this project to understand MP2RAGE more deeply by implementing Marques et al. (2010) myself. There are other implementations but I think this one is unique in the following ways:
- It is Python.
- It is minimalist by design (only using functions, and Numpy as a core dependency).
- The functions have extensive documentation in their docstrings.
- It is build to teach the details of MP2RAGE T1 mapping (first to myself and maybe in the future to others :) ).
- [TODO] It has a simple command-line interface for users with no programming or Python experience.
| Package | Tested version |
|---|---|
| Python | 3.6 |
| NumPy | 1.17.2 |
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By using pip TODO: Register to pypi upon first release.
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By cloning this repository
git clone https://github.com/ofgulban/mp2ragelib.git
cd mp2ragelib
python setup.py install
TODO: Explore the scripts provided within scripts folder.
TODO: Implement
This project is licensed under BSD-3-Clause.
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Marques, J. P., Kober, T., Krueger, G., van der Zwaag, W., Van de Moortele, P.-F., Gruetter, R. (2010). MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field. NeuroImage, 49(2), 1271–1281. <https://doi.org/10.1016/j.neuroimage.2009.10.002>
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[TODO] Marques, J. P., Gruetter, R. (2013). New developments and applications of the MP2RAGE sequence--focusing the contrast and high spatial resolution R1 mapping. PloS One, 8(7), e69294. <https://doi.org/10.1371/journal.pone.0069294>
This project is inspired by these earlier implementations: