kwneuro.masks
=============

.. py:module:: kwneuro.masks


Functions
---------

.. autoapisummary::

   kwneuro.masks.brain_extract
   kwneuro.masks.brain_extract_dwi_batch
   kwneuro.masks.brain_extract_structural_batch


Module Contents
---------------

.. py:function:: brain_extract(volume: kwneuro.resource.VolumeResource, output_path: kwneuro.util.PathLike, *, sequential: bool = False) -> kwneuro.io.NiftiVolumeResource

   Run brain extraction on a single volume using HD-BET.

   :param volume: Input volume to extract a brain mask from.
   :param output_path: Output path for the brain mask.

   Returns the computed brain mask.


.. py:function:: brain_extract_dwi_batch(cases: list[tuple[kwneuro.dwi.Dwi, pathlib.Path]], *, sequential: bool = False) -> list[kwneuro.io.NiftiVolumeResource]

   Run brain extraction on a batch of DWI cases.
   HD-BET does not run in parallel, but it does have some initialization time so it helps to run cases in batches.

   :param cases: A list of pairs each consisting of an input Dwi and desired output path for the mask.
   :param sequential: Pass through to :func:`_run_hd_bet`. Set to True
       when running inside an embedded Python that can't safely
       ``multiprocessing.spawn`` (e.g. 3D Slicer's bundled Python).
       Default False preserves the parallelised behaviour.
       The mean b0 of each DWI is used as the input to HD-BET.

   Returns a list of computed brain masks that is in correspondence with the list of input `cases`.


.. py:function:: brain_extract_structural_batch(cases: list[tuple[kwneuro.structural.StructuralImage, pathlib.Path]], *, sequential: bool = False) -> list[kwneuro.io.NiftiVolumeResource]

   Run brain extraction on a batch of structural image cases.
   HD-BET does not run in parallel, but it does have some initialization time so it helps to run cases in batches.

   :param cases: A list of pairs each consisting of an input StructuralImage and desired output path for the mask.
   :param sequential: Pass through to :func:`_run_hd_bet`. Set to True
   when running inside an embedded Python that can't safely
   ``multiprocessing.spawn`` (e.g. 3D Slicer's bundled Python).
   Default False preserves the parallelised behaviour.

   Returns a list of computed brain masks that is in correspondence with the list of input `cases`.