sksurgerytorch.models.volume_to_surface module

V2SNet Model Impementation

class sksurgerytorch.models.volume_to_surface.Volume2SurfaceCNN(mask: bool = True, weights: str = None, grid_size: int = 64)

Bases: object

Class to encapsulate network form ‘Non-Rigid Volume to Surface Registration using a Data-Driven Biomechanical Model’.

Thanks to Micha Pfieffer, for their network implementation.

Parameters:

• mask (bool) – If true, use masking
• weights (str) – Path to trained model weights (.tar file)

predict(preoperative: numpy.ndarray, intraoperative: numpy.ndarray) → numpy.ndarray

Predict the displacement field between model and surface.

Parameters:

• preoperative (np.ndarray) – Preoperative surface/point cloud
• intraoperative (np.ndarray) – Intraoperative surface/point cloud

Returns:

Displacement field

Return type:

np.ndarray