| { |
| "model_type": "vesselboost-unet3d", |
| "framework": "pytorch", |
| "task": "image-segmentation", |
| "architecture": { |
| "class_name": "models.unet_3d.Unet", |
| "spatial_dimensions": 3, |
| "input_channels": 1, |
| "output_channels": 1, |
| "base_filters": 16, |
| "encoder_stages": 4, |
| "decoder_stages": 4, |
| "convolution_kernel_size": [3, 3, 3], |
| "output_kernel_size": [1, 1, 1], |
| "normalization": "batch_norm_3d", |
| "activation": "relu", |
| "output_activation": "sigmoid_at_inference" |
| }, |
| "input": { |
| "format": "NIfTI", |
| "contrasts": [ |
| "TOF-MRA", |
| "T2*-weighted MRI (experimental checkpoint only)" |
| ], |
| "patch_size": [64, 64, 64], |
| "default_patch_stride": [64, 64, 64] |
| }, |
| "preprocessing": { |
| "resize_target": "each spatial dimension is at least 64 and a multiple of 64", |
| "resize_interpolation": "nearest_neighbor", |
| "intensity_transform": { |
| "name": "z_score_standardization", |
| "scope": "whole_volume", |
| "formula": "(x - mean(x)) / std(x)", |
| "constant_volume_result": "zeros" |
| }, |
| "optional_operations": [ |
| "N4 bias-field correction", |
| "denoising", |
| "brain extraction with separately distributed SynthStrip weights" |
| ] |
| }, |
| "postprocessing": { |
| "probability_threshold": 0.1, |
| "connected_component_minimum_voxels": 10, |
| "connected_component_connectivity": 26, |
| "prediction_resize_interpolation": "nearest_neighbor" |
| }, |
| "checkpoint_format": "PyTorch state_dict ZIP serialization", |
| "compatible_vesselboost": { |
| "version": "2.0.5", |
| "git_tag": "v2.0.5", |
| "git_commit": "3f028bbd6784c8fac82ac872a70aa06de2e162ae", |
| "source_url": "https://github.com/KMarshallX/VesselBoost/tree/v2.0.5" |
| } |
| } |
|
|
