| { | |
| "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json", | |
| "version": "1.1.4", | |
| "changelog": { | |
| "1.1.4": "enhance metadata with improved descriptions and task specification", | |
| "1.1.3": "update to huggingface hosting and fix missing dependencies", | |
| "1.1.2": "update issue for IgniteInfo", | |
| "1.1.1": "enable tensorrt", | |
| "1.1.0": "update to use monai 1.4, model ckpt not changed, rm GenerativeAI repo", | |
| "1.0.9": "update to use monai 1.3.1", | |
| "1.0.8": "define arg for output file and put infer logic into a function", | |
| "1.0.7": "update AddChanneld with EnsureChannelFirstd", | |
| "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": "1.4.0", | |
| "pytorch_version": "2.4.0", | |
| "numpy_version": "1.24.4", | |
| "required_packages_version": { | |
| "nibabel": "5.2.1", | |
| "lpips": "0.1.4", | |
| "tensorboard": "2.17.0", | |
| "einops": "0.7.0", | |
| "pytorch-ignite": "0.4.11" | |
| }, | |
| "supported_apps": {}, | |
| "name": "BraTS MRI Axial Slices Latent Diffusion Generation", | |
| "task": "Conditional Synthesis of Brain MRI Axial Slices", | |
| "description": "Latent diffusion model that synthesizes 2D brain MRI axial slices (240x240 pixels) from Gaussian noise, trained on the BraTS dataset. The model processes 1-channel latent space features (64x64) and generates FLAIR sequences with 1mm in-plane resolution, capturing diverse tumor and brain tissue appearances.", | |
| "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" | |
| } | |
| } | |
| } | |
| }, | |
| "network_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" | |
| } | |
| } | |
| } | |
| } | |
| } | |