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BraTS

Python Versions Stable Version Documentation Status tests codecov License

Providing the top performing algorithms from the Brain Tumor Segmentation (BraTS) challenges, through an easy to use Python API powered by docker.

Features

  • Access to top-performing algorithms from recent BraTS challenges
  • Easy-to-use minimal API
  • Extensive documentation and examples

Installation

With a Python 3.8+ environment, you can install brats directly from PyPI:

pip install brats

Important

To run brats you require a Docker installation.
Many algorithms also require GPU support (NVIDIA Docker).
In case you do not have access to a Cuda-capable GPU, the overview tables in the Available Algorithms and Usage section indicate which algorithms are CPU compatible.

Docker and NVIDIA Container Toolkit Setup

Available Algorithms and Usage

Segmentation

Adult Glioma Segmentation 
from brats import AdultGliomaSegmenter
from brats.constants import AdultGliomaAlgorithms

segmenter = AdultGliomaSegmenter(algorithm=AdultGliomaAlgorithms.BraTS23_1, cuda_devices="0")
# these parameters are optional, by default the winning algorithm will be used on cuda:0
segmenter.infer_single(
    t1c="path/to/t1c.nii.gz",
    t1n="path/to/t1n.nii.gz",
    t2f="path/to/t2f.nii.gz",
    t2w="path/to/t2w.nii.gz",
    output_file="segmentation.nii.gz",
)

Class: brats.AdultGliomaSegmenter (Docs)

Year Rank Author Paper CPU Support Key Enum
2023 1st André Ferreira, et al. Link ❌ BraTS23_1
2023 2nd Andriy Myronenko, et al. N/A ❌ BraTS23_2
2023 3rd Fadillah Adamsyah Maani, et al. N/A ❌ BraTS23_3
BraTS-Africa Segmentation 
from brats import AfricaSegmenter
from brats.constants import AfricaAlgorithms

segmenter = AfricaSegmenter(algorithm=AfricaAlgorithms.BraTS23_1, cuda_devices="0")
# these parameters are optional, by default the winning algorithm will be used on cuda:0
segmenter.infer_single(
    t1c="path/to/t1c.nii.gz",
    t1n="path/to/t1n.nii.gz",
    t2f="path/to/t2f.nii.gz",
    t2w="path/to/t2w.nii.gz",
    output_file="segmentation.nii.gz",
)

Class: brats.AfricaSegmenter (Docs)

Year Rank Author Paper CPU Support Key Enum
2023 1st Andriy Myronenko, et al. TODO ❌ BraTS23_1
2023 2nd Alyssa R Amod, et al. N/A ❌ BraTS23_2
2023 3rd Ziyan Huang, et al. N/A ✅ BraTS23_3
Meningioma Segmentation 
from brats import MeningiomaSegmenter
from brats.constants import MeningiomaAlgorithms

segmenter = MeningiomaSegmenter(algorithm=MeningiomaAlgorithms.BraTS23_1, cuda_devices="0")
# these parameters are optional, by default the winning algorithm will be used on cuda:0
segmenter.infer_single(
    t1c="path/to/t1c.nii.gz",
    t1n="path/to/t1n.nii.gz",
    t2f="path/to/t2f.nii.gz",
    t2w="path/to/t2w.nii.gz",
    output_file="segmentation.nii.gz",
)

Class: brats.MeningiomaSegmenter (Docs)

Year Rank Author Paper CPU Support Key Enum
2023 1st Andriy Myronenko, et al. N/A ❌ BraTS23_1
2023 2nd Ziyan Huang, et al. N/A ✅ BraTS23_2
2023 3rd Zhifan Jiang et al. N/A ❌ BraTS23_3
Brain Metastases Segmentation 
from brats import MetastasesSegmenter
from brats.constants import MetastasesAlgorithms

segmenter = MetastasesSegmenter(algorithm=MetastasesAlgorithms.BraTS23_1, cuda_devices="0")
# these parameters are optional, by default the winning algorithm will be used on cuda:0
segmenter.infer_single(
    t1c="path/to/t1c.nii.gz",
    t1n="path/to/t1n.nii.gz",
    t2f="path/to/t2f.nii.gz",
    t2w="path/to/t2w.nii.gz",
    output_file="segmentation.nii.gz",
)

Class: brats.MetastasesSegmenter (Docs)

Year Rank Author Paper CPU Support Key Enum
2023 1st Andriy Myronenko, et al. N/A ❌ BraTS23_1
2023 2nd Siwei Yang, et al. N/A ❌ BraTS23_2
2023 3rd Ziyan Huang, et al. N/A ✅ BraTS23_3
Pediatric Segmentation 
from brats import PediatricSegmenter
from brats.constants import PediatricAlgorithms

segmenter = PediatricSegmenter(algorithm=PediatricAlgorithms.BraTS23_1, cuda_devices="0")
# these parameters are optional, by default the winning algorithm will be used on cuda:0
segmenter.infer_single(
    t1c="path/to/t1c.nii.gz",
    t1n="path/to/t1n.nii.gz",
    t2f="path/to/t2f.nii.gz",
    t2w="path/to/t2w.nii.gz",
    output_file="segmentation.nii.gz",
)

Class: brats.PediatricSegmenter (Docs)

Year Rank Author Paper CPU Support Key Enum
2023 1st Zhifan Jiang et al. N/A ❌ BraTS23_1
2023 2nd Andriy Myronenko, et al. N/A ❌ BraTS23_2
2023 3rd Yubo Zhou N/A ❌ BraTS23_3

Inpainting

Inpainting 
from brats import Inpainter
from brats.constants import InpaintingAlgorithms

inpainter = Inpainter(algorithm=InpaintingAlgorithms.BraTS24_1, cuda_devices="0")
inpainter.infer_single(
    t1n="path/to/voided_t1n.nii.gz",
    mask="path/to/mask.nii.gz",
    output_file="inpainting.nii.gz",
)

Class: brats.Inpainter (Docs)

Year Rank Author Paper CPU Support Key Enum
2024 1st Ke Chen, Juexin Zhang, Ying Weng N/A ✅ BraTS24_1
2024 2nd André Ferreira, et al. N/A ❌ BraTS24_2
2024 3rd Team SMINT N/A ❌ BraTS24_3
2023 1st Juexin Zhang, et al. N/A ✅ BraTS23_1
2023 2nd Alicia Durrer, et al. N/A ❌ BraTS23_2
2023 3rd Jiayu Huo, et al. N/A ✅ BraTS23_3

Tip

For a full notebook example with more details please check here:
nbviewer

Citation

If you use BraTS in your research, please cite it to support the development!

TODO: citation will be added asap

Contributing

We welcome all kinds of contributions from the community!

Reporting Bugs, Feature Requests and Questions

Please open a new issue here.

Code contributions

Nice to have you on board! Please have a look at our CONTRIBUTING.md file.