nnU-Net plan: nnUNetPlans
Dataset: Dataset003_Liver
Experiment planner: ExperimentPlanner
Label manager: LabelManager
Image reader/writer: SimpleITKIO
Original median spacing after transpose: 1, 0.767578125, 0.767578125
Original median shape after transpose: 432, 512, 512
Transpose forward: 0, 1, 2
Transpose backward: 0, 1, 2

Configurations:
2d_p256: inherits_from: 2d
patch_size: 256, 256
2d: data_identifier: nnUNetPlans_2d
preprocessor_name: DefaultPreprocessor
batch_size: 12
patch_size: 512, 512
median_image_size_in_voxels: 512, 512
spacing: 0.767578125, 0.767578125
normalization_schemes: CTNormalization
use_mask_for_norm: no
UNet_class_name: PlainConvUNet
UNet_base_num_features: 32
n_conv_per_stage_encoder: 2, 2, 2, 2, 2, 2, 2, 2
n_conv_per_stage_decoder: 2, 2, 2, 2, 2, 2, 2
num_pool_per_axis: 7, 7
pool_op_kernel_sizes: 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2
conv_kernel_sizes: 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3
unet_max_num_features: 512
resampling_fn_data: resample_data_or_seg_to_shape
resampling_fn_seg: resample_data_or_seg_to_shape
resampling_fn_data_kwargs: is_seg: no
order: 3
order_z: 0
resampling_fn_seg_kwargs: is_seg: yes
order: 1
order_z: 0
resampling_fn_probabilities: resample_data_or_seg_to_shape
resampling_fn_probabilities_kwargs: is_seg: no
order: 1
order_z: 0
batch_dice: yes
3d_lowres: data_identifier: nnUNetPlans_3d_lowres
preprocessor_name: DefaultPreprocessor
batch_size: 2
patch_size: 128, 128, 128
median_image_size_in_voxels: 193, 205, 205
spacing: 2.5000803453253524, 1.9190069838141859, 1.9190069838141859
normalization_schemes: CTNormalization
use_mask_for_norm: no
UNet_class_name: PlainConvUNet
UNet_base_num_features: 32
n_conv_per_stage_encoder: 2, 2, 2, 2, 2, 2
n_conv_per_stage_decoder: 2, 2, 2, 2, 2
num_pool_per_axis: 5, 5, 5
pool_op_kernel_sizes: 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2
conv_kernel_sizes: 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3
unet_max_num_features: 320
resampling_fn_data: resample_data_or_seg_to_shape
resampling_fn_seg: resample_data_or_seg_to_shape
resampling_fn_data_kwargs: is_seg: no
order: 3
order_z: 0
resampling_fn_seg_kwargs: is_seg: yes
order: 1
order_z: 0
resampling_fn_probabilities: resample_data_or_seg_to_shape
resampling_fn_probabilities_kwargs: is_seg: no
order: 1
order_z: 0
batch_dice: no
next_stage: 3d_cascade_fullres
3d_fullres: data_identifier: nnUNetPlans_3d_fullres
preprocessor_name: DefaultPreprocessor
batch_size: 2
patch_size: 128, 128, 128
median_image_size_in_voxels: 482, 512, 512
spacing: 1, 0.767578125, 0.767578125
normalization_schemes: CTNormalization
use_mask_for_norm: no
UNet_class_name: PlainConvUNet
UNet_base_num_features: 32
n_conv_per_stage_encoder: 2, 2, 2, 2, 2, 2
n_conv_per_stage_decoder: 2, 2, 2, 2, 2
num_pool_per_axis: 5, 5, 5
pool_op_kernel_sizes: 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2
conv_kernel_sizes: 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3
unet_max_num_features: 320
resampling_fn_data: resample_data_or_seg_to_shape
resampling_fn_seg: resample_data_or_seg_to_shape
resampling_fn_data_kwargs: is_seg: no
order: 3
order_z: 0
resampling_fn_seg_kwargs: is_seg: yes
order: 1
order_z: 0
resampling_fn_probabilities: resample_data_or_seg_to_shape
resampling_fn_probabilities_kwargs: is_seg: no
order: 1
order_z: 0
batch_dice: yes
3d_cascade_fullres: inherits_from: 3d_fullres
previous_stage: 3d_lowres

Foreground intensity properties per channel:
0: max: 5420
mean: 99.48007202148438
median: 101
min: -983
percentile_00_5: -15
percentile_99_5: 197
std: 37.13840103149414