wmh-segmentation

Automate white matter hyperintensity segmentation by providing co-registered FLAIR and T1w NIfTI images to run the MARS-WMH nnU-Net Docker pipeline, which outputs a ready-to-use NIfTI segmentation mask.

Yes, GPU support is required to execute the MARS-WMH nnU-Net Docker container for WMH segmentation, as the pipeline checks for GPU readiness and Docker dependencies before processing your MRI data.

Automated WMH segmentation requires a paired FLAIR and T1w NIfTI image without contrast, which the pipeline validates for format and co-registration before executing the Docker workflow.

The MARS-WMH nnU-Net pipeline orchestrates workspace preparation by validating inputs, checking dependencies, preparing the environment, and executing through claw-shell to ensure a reproducible WMH segmentation run.

The output format from white matter hyperintensity segmentation is a NIfTI mask, delivered with a structured completion status report and exact output paths for immediate downstream use.

Yes, the WMH segmentation workflow validates the co-registration of your FLAIR and T1w NIfTI inputs before executing the MARS-WMH nnU-Net pipeline to ensure accurate processing.