Metadata-Version: 2.1
Name: brainles_preprocessing
Version: 0.0.18
Summary: TODO.
Home-page: https://github.com/BrainLesion/preprocessing
License: AGPL-3.0
Keywords: brain tumor,glioma,BraTS,skullstripping,brain extraction
Author: Florian Kofler
Author-email: florian.kofler@tum.de
Maintainer: Florian Kofler
Maintainer-email: florian.kofler@tum.de
Requires-Python: >=3.10,<4.0
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: BrainLes-HD-BET (>=0.0.5)
Requires-Dist: auxiliary (>=0.0.40,<0.0.41)
Requires-Dist: nibabel (>=3.2.1,<4.0.0)
Requires-Dist: numpy (>=1.23.0,<2.0.0)
Requires-Dist: path (>=16.2.0,<17.0.0)
Requires-Dist: pathlib (>=1.0.1,<2.0.0)
Requires-Dist: rich (>=13.6.0,<14.0.0)
Requires-Dist: tqdm (>=4.64.1,<5.0.0)
Requires-Dist: ttictoc (>=0.5.6,<0.6.0)
Project-URL: Repository, https://github.com/BrainLesion/preprocessing
Description-Content-Type: text/markdown

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# BrainLes-Preprocessing

`BrainLes-Preprocessing` is a comprehensive tool tailored for preprocessing tasks in medical imaging, with a current focus on brain MRIs. Here's what it can currently do:

- **Co-registration using NiftyReg**: Aligning two images or series of images. While `NiftyReg` is the current tool used for co-registration, our architecture allows for potential extensions with other tools in the future.
- **Atlas Registration**: Maps images to a standard atlas for consistent spatial referencing.
- **Transformation**: Adjusts the image based on certain parameters.
- **Skull-stripping in BRATS-space**: Removes non-brain tissue from MRI data.
- **Apply Masking**: Applies a mask to an image, highlighting or hiding specific parts of it.

The outcome of this processing sequence is a set of 4 NIFTI images, skull-stripped in BRATS-space. These results are then saved to the provided path.

## Atlas Reference

We use the SRI-24 atlas from this [publication](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2915788/)

## Installation

With a Python 3.10+ environment you can install directly from [pypi.org](https://pypi.org/project/brainles-preprocessing/):

```
pip install brainles-preprocessing
```

