monai
medical
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unify dataset dir in different configs
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{
"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_generator_ldm_20230507.json",
"version": "1.0.2",
"changelog": {
"1.0.2": "unify dataset dir in different configs",
"1.0.1": "update dependency, update trained model weights",
"1.0.0": "Initial release"
},
"monai_version": "1.2.0rc5",
"pytorch_version": "1.13.1",
"numpy_version": "1.22.2",
"optional_packages_version": {
"nibabel": "5.1.0",
"lpips": "0.1.4"
},
"name": "BraTS MRI image latent diffusion generation",
"task": "BraTS MRI image synthesis",
"description": "A generative model for creating 3D brain MRI from Gaussian noise based on BraTS dataset",
"authors": "MONAI team",
"copyright": "Copyright (c) MONAI Consortium",
"data_source": "http://medicaldecathlon.com/",
"data_type": "nibabel",
"image_classes": "Flair brain MRI with 1.1x1.1x1.1 mm voxel size",
"eval_metrics": {},
"intended_use": "This is a research tool/prototype and not to be used clinically",
"references": [],
"autoencoder_data_format": {
"inputs": {
"image": {
"type": "image",
"format": "image",
"num_channels": 1,
"spatial_shape": [
112,
128,
80
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true
}
},
"outputs": {
"pred": {
"type": "image",
"format": "image",
"num_channels": 1,
"spatial_shape": [
112,
128,
80
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true,
"channel_def": {
"0": "image"
}
}
}
},
"generator_data_format": {
"inputs": {
"latent": {
"type": "noise",
"format": "image",
"num_channels": 8,
"spatial_shape": [
36,
44,
28
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true
},
"condition": {
"type": "timesteps",
"format": "timesteps",
"num_channels": 1,
"spatial_shape": [],
"dtype": "long",
"value_range": [
0,
1000
],
"is_patch_data": false
}
},
"outputs": {
"pred": {
"type": "feature",
"format": "image",
"num_channels": 8,
"spatial_shape": [
36,
44,
28
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true,
"channel_def": {
"0": "image"
}
}
}
}
}