# Reva Coregistration
A Python package for image coregistration and coordinate transformation, specifically designed for medical imaging applications.
## Features
- **Image Coregistration**: Align images using landmark-based transformations
- **Coordinate Transformation**: Convert coordinates between different image spaces
- **Non-linear Warping**: Apply advanced warping techniques for precise alignment
- **Slice Management**: Handle multi-slice image data
- **Tile Processing**: Efficient processing of large images using tiling
## Installation
```bash
pip install reva-coregistration
```
## Quick Start
```python
from reva_coregistration import get_associated_coordinates
# Define landmarks for coregistration
landmarks = [
{"target": {"x": 100, "y": 200}, "source": {"x": 150, "y": 250}},
{"target": {"x": 300, "y": 400}, "source": {"x": 350, "y": 450}},
# ... more landmark pairs
]
# Get associated coordinates
coordinates = get_associated_coordinates(
x_percentage=0.5,
y_percentage=0.3,
source_image_width=1024,
source_image_height=768,
source_is_photograph=True,
target_image_width=2048,
target_image_height=1536,
apply_nonlinear_warping=True,
landmarks=landmarks
)
print(coordinates)
```
## Documentation
For detailed documentation, please visit the [project repository](https://github.com/yourusername/reva-coregistration).
## Development
To set up the development environment:
```bash
git clone https://github.com/yourusername/reva-coregistration.git
cd reva-coregistration
pip install -e ".[dev]"
```
Run tests:
```bash
pytest
```
## License
This project is licensed under the MIT License - see the LICENSE file for details.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
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