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Python library to generate regressors for and compute Cerebrovascular Reactivity and lag maps.

Project description

phys2cvr

Latest version Release date Auto Release

Latest DOI Licensed Apache 2.0

Documentation Status

Latest version Supports python version

All Contributors

A python-based tool to generate regressor for and/or estimate CVR maps and their lag.

The project is currently under development stage alpha. Any suggestion/bug report is welcome! Feel free to open an issue.

This project follows the all-contributors specification. Contributions of any kind welcome!

Documentation

Full documentation here

Cite

If you use phys2cvr in your work, please cite either the all-time Zenodo DOI general Zenodo DOI or the Zenodo DOI related to the version you are using. Please cite the following paper(s) too:

Moia, S., Stickland, R. C., Ayyagari, A., Termenon, M., Caballero-Gaudes, C., & Bright, M. G. (2020). Voxelwise optimization of hemodynamic lags to improve regional CVR estimates in breath-hold fMRI. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 1489–1492). Montreal, QC, Canada: IEEE. https://doi.org/10.1109/EMBC44109.2020.9176225

If you are using the --brightspin configuration option:

Moia, S., Termenon, M., Uruñuela, E., Chen, G., Stickland, R. C., Bright, M. G., & Caballero-Gaudes, C. (2021). ICA-based denoising strategies in breath-hold induced cerebrovascular reactivity mapping with multi echo BOLD fMRI. NeuroImage, 233, 117914. https://doi.org/10.1016/j.neuroimage.2021.117914

If you are using the --brightspin-clinical configuration option:

Stickland, R. C., Zvolanek, K. M., Moia, S., Ayyagari, A., & Bright, M. G. (2021). A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function. Supplementary Material. Neuroimage.

If you are using the --baltimore-lag configuration option:

Liu, P., Li, Y., Pinho, M., Park, D. C., Welch, B. G., & Lu, H. (2017). Cerebrovascular reactivity mapping without gas challenges. NeuroImage, 146(November 2016), 320–326. https://doi.org/10.1016/j.neuroimage.2016.11.054

If you are using the --baltimore configuration option, please cite only the Zenodo DOI and the last listed paper.

Installation

Instructions here

Developer installation

(Potential) Contributors, instead see here!

Run/use phys2cvr

You can run the phys2cvr workflow in a shell session (or in your code) - just follow the help or see here:

phys2cvr --help

Alternatively, you can use phys2cvr as a module in a python session (or within your python script):

import phys2cvr as p2c

p2c.__version__

Full API here

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Stefano Moia
Stefano Moia

💻 🤔 🚇 📆
Kristina Zvolanek
Kristina Zvolanek

💻 🐛 🚇
Becca Clements
Becca Clements

🐛 💻 📓
Andrew Vigotsky
Andrew Vigotsky

💻
ccomellalue
ccomellalue

💻 🤔
merelvdthiel
merelvdthiel

📖
razkin
razkin

🎨 📖 ⚠️

License

Copyright 2021-2026, Stefano Moia & phys2cvr contributors.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

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