res_unet_3d(pretrained: bool = False, overrides: object = {})3-D ResUNet — volumetric residual U-Net.
Builds a 3-D U-Net with residual DoubleConv blocks: the volumetric
counterpart to res_unet_2d. Useful for deeper variants on
biomedical volumes where the residual shortcut materially helps
optimisation stability.
Model Size
Parameters
pretrainedbool= FalseReserved for future pretrained-weight loading. Currently ignored.
**overridesobject= {}Keyword overrides forwarded into
UNetConfig.Returns
UNetForSemanticSegmentationSegmentation model with the 3-D ResUNet configuration applied
(or with overrides merged on top of it).
Notes
Combines the 3-D U-Net topology of Cicek et al. (MICCAI 2016) with the residual DoubleConv blocks of Zhang et al. (2018).
Examples
>>> import lucid
>>> from lucid.models.vision.unet import res_unet_3d
>>> model = res_unet_3d()
>>> x = lucid.randn(1, 1, 64, 64, 64)
>>> out = model(x)
>>> out.logits.shape
(1, 2, 64, 64, 64)