File size: 2,441 Bytes
57decc6 699e3ee 57decc6 699e3ee a59a63a 57decc6 a59a63a 699e3ee 57decc6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
{
"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json",
"version": "1.0.3",
"changelog": {
"1.0.3": "enhance metadata with improved descriptions",
"1.0.2": "add missing dependencies",
"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": {
"pyyaml": "6.0.2"
},
"name": "MedNIST DDPM Hand X-ray Generation",
"task": "Synthetic Hand X-ray Image Generation via DDPM",
"description": "A denoising diffusion probabilistic model (DDPM) that synthesizes hand X-ray images based on the MedNIST dataset. The model learns the underlying distribution of the dataset through an iterative denoising process, demonstrating the capabilities of diffusion models in medical image synthesis. Features progressive noise-to-image generation with fine-grained control over the generation process.",
"authors": "Walter Hugo Lopez Pinaya, Mark Graham, and Eric Kerfoot",
"copyright": "Copyright (c) KCL",
"references": [],
"intended_use": "This is suitable for research purposes only.",
"image_classes": "Single channel magnitude data.",
"data_source": "MedNIST",
"network_data_format": {
"inputs": {
"image": {
"type": "image",
"format": "magnitude",
"modality": "xray",
"num_channels": 1,
"spatial_shape": [
1,
64,
64
],
"dtype": "float32",
"value_range": [],
"is_patch_data": false,
"channel_def": {
"0": "image"
}
}
},
"outputs": {
"pred": {
"type": "image",
"format": "magnitude",
"modality": "xray",
"num_channels": 1,
"spatial_shape": [
1,
64,
64
],
"dtype": "float32",
"value_range": [],
"is_patch_data": false,
"channel_def": {
"0": "image"
}
}
}
}
}
|