| { | |
| "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json", | |
| "version": "0.4.6", | |
| "changelog": { | |
| "0.4.6": "enhance metadata with improved descriptions", | |
| "0.4.5": "update to huggingface hosting", | |
| "0.4.4": "initial bundle assemblage." | |
| }, | |
| "monai_version": "1.3.0", | |
| "pytorch_version": "2.1.0", | |
| "numpy_version": "1.22.2", | |
| "optional_packages_version": { | |
| "fire": "0.4.0", | |
| "nibabel": "4.0.1", | |
| "pytorch-ignite": "0.4.11" | |
| }, | |
| "name": "Pediatric Abdominal CT Segmentation", | |
| "task": "3D Segmentation of Liver, Spleen and Pancreas in Pediatric Abdominal CT", | |
| "description": "A 3D segmentation model for liver, spleen, and pancreas in pediatric abdominal CT images. The model processes 96x96x96 pixel patches and provides segmentation masks. Pre-trained on TotalSegmentator, TCIA and BTCV datasets and fine-tuned on Cincinnati Children's Healthy Pediatric Dataset.", | |
| "authors": "Cincinnati Children's (CCHMC) - CAIIR Center (https://www.cincinnatichildrens.org/research/divisions/r/radiology/labs/caiir)", | |
| "copyright": "Copyright (c) MONAI Consortium", | |
| "data_source": "TotalSegmentator, TCIA and BTCV dataset public data", | |
| "data_type": "nifti", | |
| "image_classes": "single channel 3D data HU thresholded and clipped to a range of 0 to 1", | |
| "label_classes": "single channel data, 1 is liver, 2 is spleen, 3 is pancreas and 0 is everything else", | |
| "pred_classes": "single channel data, 1 is liver, 2 is spleen, 3 is pancreas and 0 is everything else", | |
| "eval_metrics": { | |
| "TS_mean_dice": 0.9, | |
| "TCIA_mean_dice": 0.87, | |
| "CCHMC_mean_dice": 0.89 | |
| }, | |
| "intended_use": "Pediatric model - Validation on institutional data required before clinical use", | |
| "references": [ | |
| "MedArxiv paper: url to be updated" | |
| ], | |
| "network_data_format": { | |
| "inputs": { | |
| "image": { | |
| "type": "image", | |
| "format": "hounsfield", | |
| "modality": "CT", | |
| "num_channels": 1, | |
| "spatial_shape": [ | |
| 96, | |
| 96, | |
| 96 | |
| ], | |
| "dtype": "float32", | |
| "value_range": [ | |
| 0, | |
| 1 | |
| ], | |
| "is_patch_data": true, | |
| "channel_def": { | |
| "0": "image" | |
| } | |
| } | |
| }, | |
| "outputs": { | |
| "pred": { | |
| "type": "image", | |
| "format": "segmentation", | |
| "num_channels": 4, | |
| "spatial_shape": [ | |
| 96, | |
| 96, | |
| 96 | |
| ], | |
| "dtype": "float32", | |
| "value_range": [ | |
| 0, | |
| 1, | |
| 2, | |
| 3 | |
| ], | |
| "is_patch_data": true, | |
| "label_def": { | |
| "0": "background", | |
| "1": "liver", | |
| "2": "spleen", | |
| "3": "pancreas" | |
| } | |
| } | |
| } | |
| } | |
| } | |