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{
"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
"version": "1.0.2",
"changelog": {
"1.0.2": "enhanced metadata with improved descriptions and task specification",
"1.0.1": "update to huggingface hosting",
"1.0.0": "Initial release"
},
"monai_version": "1.4.0",
"pytorch_version": "2.5.1",
"numpy_version": "1.26.4",
"required_packages_version": {
"transformers": "4.46.3",
"einops": "0.8.1",
"pillow": "10.4.0"
},
"name": "Chest X-ray Latent Diffusion Synthesis",
"task": "Conditional Synthesis of Chest X-ray Images with Pathology Control",
"description": "A latent diffusion model that generates 512x512 pixel chest X-ray images from a 64x64x77 dimensional latent space. The model processes text-based condition inputs through a 1024-dimensional context vector, enabling controlled generation of X-rays with specific pathological features.",
"copyright": "Copyright (c) MONAI Consortium",
"authors": "Walter Hugo Lopez Pinaya, Mark Graham, Eric Kerfoot, Virginia Fernandez",
"data_source": "https://physionet.org/content/mimic-cxr-jpg/2.0.0/",
"data_type": "image",
"image_classes": "Radiography (X-ray) with 512 x 512 pixels",
"intended_use": "This is a research tool/prototype and not to be used clinically",
"network_data_format": {
"inputs": {
"latent_representation": {
"type": "image",
"format": "magnitude",
"modality": "CXR",
"num_channels": 3,
"spatial_shape": [
77,
64,
64
],
"dtype": "float32",
"value_range": [],
"is_patch_data": false
},
"timesteps": {
"format": "magnitude",
"num_channels": 1,
"spatial_shape": [
1
],
"type": "vector",
"value_range": [
0,
1000
],
"dtype": "long"
},
"context": {
"format": "magnitude",
"num_channels": 1024,
"spatial_shape": [
1
],
"type": "vector",
"value_range": [],
"dtype": "float32"
}
},
"outputs": {
"pred": {
"type": "image",
"format": "magnitude",
"modality": "CXR",
"num_channels": 1,
"spatial_shape": [
512,
512
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": false,
"channel_def": {
"0": "X-ray"
}
}
}
}
}
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