Welcome to the Pulmonary MRI GitHub organization! The purpose of this organization is to provide a centralized resource of software repositories supporting the development and use of pulmonary (lung) MRI. We develop open-source tools for pulmonary (lung) MRI acquisition, reconstruction, and analysis, with a focus on motion compensation and functional imaging. Modify the organization profile README to include the following: Purpose - provide a centralized resource for software repositories supporting the development and use of Pulmonary MRI. This is open to any researchers to join and for any repository to listed Community - include requests to join the organization, and requests to have your repository listed by the organization Listing of all public repsoitories with short description and, if available, associated publication
This effort is led by MRI researchers dedicated to advancing pulmonary MRI techniques. The scope of the repositories is intended to support any pulmonary MRI methods, including (but not limited to) image reconstruction algorithms, motion management strategies, pulse sequences, structural imaging methods, functional lung imaging methods, and hyperpolarized gas (e.g. Xe-129) methods.
| Repository | Description | Language |
|---|---|---|
| imoco_recon | Iterative Motion Compensation (iMoCo) reconstruction for MRI | MATLAB / Python |
| MoCoLoR | Motion-compensated low-rank reconstruction for simultaneous structural and functional UTE lung MRI | Python |
| pulmonary-MRI-reconstruction | Tools for reconstructing pulmonary MRI datasets to manage motion | MATLAB |
| reproducibility | Reproducibility tools and scripts | Python |
| philips_recon | Reconstruction pipelines for Philips MRI systems | Jupyter Notebook |
- Motion-compensated MRI reconstruction — algorithms that correct for respiratory motion during acquisition
- Ultrashort echo time (UTE) imaging — techniques for imaging the lung parenchyma
- Structural and functional lung MRI — combined assessment of lung structure and ventilation/perfusion
- Reproducible research — code and data sharing to support open science
Key papers associated with our software:
- iMoCo: doi:10.1002/mrm.27998
- MoCoLoR: doi:10.1002/mrm.29703
We welcome contributions! Please open an issue or pull request in the relevant repository.