AFQ.nn.multiaxial
=================

.. py:module:: AFQ.nn.multiaxial


Functions
---------

.. autoapisummary::

   AFQ.nn.multiaxial.multiaxial
   AFQ.nn.multiaxial.run_multiaxial
   AFQ.nn.multiaxial.extract_brain_mask


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

.. py:function:: multiaxial(ort, img, model_sagittal, model_axial, model_coronal, consensus_model, onnx_kwargs)

   
   Perform multiaxial segmentation using three ONNX models
   and a consensus model [1].


   :Parameters:

       **img** : ndarray
           3D T1 image to segment.

       **model_sagittal** : str
           Path to sagittal ONNX model.

       **model_axial** : str
           Path to axial ONNX model.

       **model_coronal** : str
           Path to coronal ONNX model.

       **consensus_model** : str
           Path to consensus ONNX model.

       **onnx_kwargs** : dict
           ONNX kwargs to use for inference.

   :Returns:

       **pred** : ndarray
           Segmentation labels for each coordinate.









   .. rubric:: References

   [1] Birnbaum, Andrew M., et al. "Full-head segmentation of MRI
   with abnormal brain anatomy: model and data release." Journal of
   Medical Imaging 12.5 (2025): 054001-054001.

   .. only:: latex

      




   ..
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.. py:function:: run_multiaxial(ort, t1_img, onnx_kwargs)

   
   Run the multiaxial model.
















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.. py:function:: extract_brain_mask(predictions)

   
   Extract brain mask from multiaxial predictions.


   :Parameters:

       **predictions** : Nifti1Image
           Multiaxial segmentation predictions.

   :Returns:

       **bm_data** : ndarray
           Brain mask data.













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