Inpainting Algorithms

The following classes provide inpainting algorithms from several BraTS challenges.

class brats.core.inpainting_algorithms.Inpainter(algorithm: InpaintingAlgorithms = InpaintingAlgorithms.BraTS23_1, cuda_devices: str | None = '0', force_cpu: bool = False)

Bases: BraTSAlgorithm

infer_batch(data_folder: Path | str, output_folder: Path | str, log_file: Path | str | None = None, backend: Backends | None = Backends.DOCKER) → None

Perform inpainting on a batch of subjects with the provided images and save the results to the output folder.

Requires the following structure:

data_folder

┣ A

┃ ┣ A-t1n-voided.nii.gz

┃ ┣ A-mask.nii.gz

┣ B

┃ ┣ B-t1n-voided.nii.gz

┃ ┣ B-mask.nii.gz

┣ C …

Parameters:

  • data_folder (Path | str) – Folder containing the subjects with required structure

  • output_folder (Path | str) – Output folder to save the segmentations

  • log_file (Path | str, optional) – Save logs to this file

  • backend (Backends, optional) – Backend to use for inference. Defaults to Backends.DOCKER.

infer_single(t1n: Path | str, mask: Path | str, output_file: Path | str, log_file: Path | str | None = None, backend: Backends | None = Backends.DOCKER) → None

Perform inpainting task on a single subject with the provided images and save the result to the output file.

Parameters:

  • t1n (Path | str) – Path to the voided T1n image

  • mask (Path | str) – Path to the mask image

  • output_file (Path | str) – Path to save the segmentation

  • log_file (Path | str, optional) – Save logs to this file

  • backend (Backends, optional) – Backend to use for inference. Defaults to Backends.DOCKER.