https://github.com/beatawereszczynska/ti_te_wish
Simulating T1- and T2-weighted MRI images with arbitrary values of TI or TE, respectively. (Python 3)
Science Score: 23.0%
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Simulating T1- and T2-weighted MRI images with arbitrary values of TI or TE, respectively. (Python 3)
Basic Info
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Metadata Files
README.md
TITEwish
Calculating theoretical T1-weighted MRI images with arbitrary value of inversion time (TI) based on previously acquired spin echo multi-slice experiment with inversion recovery (SEMS-IR) .fid (Agilent) data. This functionality can be used to calculate many T1-weighted images, with small TI step, to find the TI value for the optimal image contrast after performing MRI imaging for just few TI values to save time.
Calculating theoretical T2-weighted MRI images with arbitrary value of echo time (TE) based on previously acquired multi-echo multi-slice (MEMS) .fid (Agilent) data. This functionality can be useful when TE needed to obtain optimal image contrast is outside the hardware limits. This can happen when using large image matrix while imaging structures with short T2.
The script can also be used for calculating T1, T2 and M0 maps without calculating theoretical images.

The user provides the data folder location and a list of desired TE or TI values. If the list is empty, only the parametric maps are calculated. The script automatically imports the data with all the parameters needed and performs computations. The user can change the value of glob_var parameter to save the maps and/or the images in global Python variable for further use (instead of just saving the image files).
The repository contains:
- Python script TITEwish.py.
- Sample FID data in sems2019040707.fid and mems2019051901.fid folders.
- Sample results in TheoreticalMRIT1w and TheoreticalMRIT2w folders.
- Graphical abstract graph_abst.png.
Reference: Collection of the sample data
Beata Wereszczyńska, Alcohol-fixed specimens for high-contrast post-mortem MRI, Forensic Imaging, Volume 25, 2021, 200449, ISSN 2666-2256, https://doi.org/10.1016/j.fri.2021.200449. (https://www.sciencedirect.com/science/article/pii/S2666225621000208)
License
The software is licensed under the MIT license. The non-software content of this project is licensed under the Creative Commons Attribution 4.0 International license. See the LICENSE file for license rights and limitations.
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Owner
- Name: Beata Wereszczyńska
- Login: BeataWereszczynska
- Kind: user
- Location: Poland
- Website: https://www.linkedin.com/in/beata-wereszczynska
- Repositories: 4
- Profile: https://github.com/BeataWereszczynska
I'm a Python enthusiast, but also an NMR and MRI physicist (PhD) with broad experience in experimental research.