BraTS

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

• Docker: Installation instructions on the official website
• NVIDIA Container Toolkit: Refer to the NVIDIA install guide and the official GitHub page

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:

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.