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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": "1.0.6",
"changelog": {
"1.0.6": "update with new lr scheduler api in inference",
"1.0.5": "fix the wrong GPU index issue of multi-node",
"1.0.4": "update with new lr scheduler api",
"1.0.3": "update required packages",
"1.0.2": "remove unused saver in inference",
"1.0.1": "fix inference folder error",
"1.0.0": "Initial release"
},
"monai_version": "1.2.0",
"pytorch_version": "1.13.1",
"numpy_version": "1.22.2",
"optional_packages_version": {
"nibabel": "5.1.0",
"lpips": "0.1.4",
"monai-generative": "0.2.2"
},
"name": "BraTS MRI axial slices latent diffusion generation",
"task": "BraTS MRI axial slices synthesis",
"description": "A generative model for creating 2D brain MRI axial slices 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 axial slices with 1x1 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": [
240,
240
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true
}
},
"outputs": {
"pred": {
"type": "image",
"format": "image",
"num_channels": 1,
"spatial_shape": [
240,
240
],
"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": 1,
"spatial_shape": [
64,
64
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true
}
},
"outputs": {
"pred": {
"type": "feature",
"format": "image",
"num_channels": 1,
"spatial_shape": [
64,
64
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true,
"channel_def": {
"0": "image"
}
}
}
}
}
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