count_parameters()
run()
unet_bottleneck_gn
unet_bottleneck_gn.forward()
unet_box_gn
unet_box_gn.forward()
unet_down
unet_down.forward()
unet_ns_gn
unet_ns_gn.forward()
unet_up
unet_up.forward()
UNet
UNet.forward()
UNet.forward_gradcp()
UNet.weight_init()
unet3d()
PatchIndex
PatchIndex.d_idx
PatchIndex.left
PatchIndex.top
TilingMeta
TilingMeta.D
TilingMeta.H_in
TilingMeta.H_pad
TilingMeta.P_per_slice
TilingMeta.W_in
TilingMeta.W_pad
TilingMeta.edge_mode
TilingMeta.n_cols
TilingMeta.n_rows
TilingMeta.neighbors
TilingMeta.pad_bottom
TilingMeta.pad_mode
TilingMeta.pad_right
TilingMeta.ph
TilingMeta.pw
TilingMeta.stride_h
TilingMeta.stride_w
TomoDatasetInfer
TomoDatasetInfer.stitch_predictions()
TomoDatasetTrain
save_normalization_value()
TomoDataset3DInfer
TomoDataset3DInfer.stitch_predictions()
TomoDataset3DTrain
geom_transform_3d()
save_normalization_value_3d()
InferenceBatchSizeOptimizer
InferenceBatchSizeOptimizer.estimate_peak_memory()
InferenceBatchSizeOptimizer.find_optimal_batch_size()
InferenceBatchSizeOptimizer.get_available_memory()
InferenceBatchSizeOptimizer.profile()
extract_sliding_window_patches_25d()
stitch_sliding_window_patches()
stitch_sliding_window_patches_core()
LCL
LCL.forward()
laplacian_batch()
laplacian_entropy_map()
laplacian_score_batch()
list_registry()
register()
search()
glob()
load_sino()
load_stack()
natural_sorted()
save_stack()
save2img()
save2img_rgb()
scale2uint8()
str2bool()
Denoise the entire CT volume using a trained Noise2Inverse model.