| { | |
| "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json", | |
| "version": "0.1.0", | |
| "changelog": { | |
| "0.1.0": "complete the model package" | |
| }, | |
| "monai_version": "0.9.0", | |
| "pytorch_version": "1.10.0", | |
| "numpy_version": "1.21.2", | |
| "optional_packages_version": { | |
| "nibabel": "3.2.1", | |
| "pytorch-ignite": "0.4.8" | |
| }, | |
| "task": "Multimodal Brain Tumor segmentation", | |
| "description": "A pre-trained model for volumetric (3D) segmentation of brain tumor subregions from multimodal MRIs based on BraTS 2018 data", | |
| "authors": "MONAI team", | |
| "copyright": "Copyright (c) MONAI Consortium", | |
| "data_source": "https://www.med.upenn.edu/sbia/brats2018/data.html", | |
| "data_type": "nibabel", | |
| "image_classes": "4 channel data, T1c, T1, T2, FLAIR at 1x1x1 mm", | |
| "label_classes": "3 channel data, channel 0 for Tumor core, channel 1 for Whole tumor, channel 2 for Enhancing tumor", | |
| "pred_classes": "3 channels data, same as label_classes", | |
| "eval_metrics": { | |
| "val_mean_dice": 0.8518, | |
| "val_mean_dice_tc": 0.8559, | |
| "val_mean_dice_wt": 0.9026, | |
| "val_mean_dice_et": 0.7905 | |
| }, | |
| "intended_use": "This is an example, not to be used for diagnostic purposes", | |
| "references": [ | |
| "Myronenko, Andriy. '3D MRI brain tumor segmentation using autoencoder regularization.' International MICCAI Brainlesion Workshop. Springer, Cham, 2018. https://arxiv.org/abs/1810.11654" | |
| ], | |
| "network_data_format": { | |
| "inputs": { | |
| "image": { | |
| "type": "image", | |
| "format": "magnitude", | |
| "modality": "MR", | |
| "num_channels": 4, | |
| "spatial_shape": [ | |
| "8*n", | |
| "8*n", | |
| "8*n" | |
| ], | |
| "dtype": "float32", | |
| "value_range": [ | |
| 0, | |
| 1 | |
| ], | |
| "is_patch_data": true, | |
| "channel_def": { | |
| "0": "image" | |
| } | |
| } | |
| }, | |
| "outputs": { | |
| "pred": { | |
| "type": "image", | |
| "format": "segmentation", | |
| "num_channels": 3, | |
| "spatial_shape": [ | |
| "8*n", | |
| "8*n", | |
| "8*n" | |
| ], | |
| "dtype": "float32", | |
| "value_range": [ | |
| 0, | |
| 1 | |
| ], | |
| "is_patch_data": true, | |
| "channel_def": { | |
| "0": "background", | |
| "1": "spleen" | |
| } | |
| } | |
| } | |
| } | |
| } | |