CloudReg is a tool for cross-modal, nonlinear, image registration between arbitrary image volumes.
Quantifying terascale multi-modal human and animal imaging data requires scalable analysis tools. We developed CloudReg, an automated, terascale, cloud-based image analysis pipeline for preprocessing and cross-modal, non-linear registration between volumetric datasets with artifacts. CloudReg was developed using cleared mouse and rat brain light-sheet microscopy images, but is also accurate in registering the following datasets to their respective atlases: in vivo human and ex vivo macaque brain magnetic resonance imaging, ex vivo murine brain micro-computed tomography. Our extensive documentation (below) can enable deployment of this tool for many other datasets/research questions.
The official documentation with usage is at https://cloudreg.neurodata.io
Please visit the Run section in the official website for more in depth usage.
CloudReg requires only a standard computer with enough RAM to support the in-memory operations since the majority of work is run in cloud services.
CloudReg is tested on the following OSes and requires Python 3:
- Linux x64
- macOS x64
Please see Setup on the official website for detailed set up information.
This project is covered under the Apache 2.0 License.
We appreciate detailed bug reports and feature requests (though we appreciate pull requests even more!). Please visit our issues page if you have questions or ideas.
If you find
CloudReg useful in your work, please cite the tool via the CloudReg paper
Chandrashekhar, V., Tward, D.J., Crowley, D. et al. CloudReg: automatic terabyte-scale cross-modal brain volume registration. Nat Methods (2021). https://doi.org/10.1038/s41592-021-01218-z