| { |
| "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json", |
| "version": "0.5.8", |
| "changelog": { |
| "0.5.8": "enhance metadata with improved descriptions", |
| "0.5.7": "update to huggingface hosting", |
| "0.5.6": "use monai 1.4 and update large files", |
| "0.5.5": "update to use monai 1.3.1", |
| "0.5.4": "add load_pretrain flag for infer", |
| "0.5.3": "update to use monai 1.3.0", |
| "0.5.2": "update the checkpoint loader logic for inference", |
| "0.5.1": "add option to validate at training start, and I/O param entries", |
| "0.5.0": "enable finetune and early stop", |
| "0.4.9": "fix orientation issue on clicks", |
| "0.4.8": "Add infer transforms to manage clicks from viewer", |
| "0.4.7": "fix the wrong GPU index issue of multi-node", |
| "0.4.6": "update to use rc7 which solves dynunet issue", |
| "0.4.5": "remove error dollar symbol in readme", |
| "0.4.4": "add RAM comsumption with Cachedataset", |
| "0.4.3": "update ONNX-TensorRT descriptions", |
| "0.4.2": "deterministic retrain benchmark, update fig links", |
| "0.4.1": "add the ONNX-TensorRT way of model conversion", |
| "0.4.0": "fix mgpu finalize issue", |
| "0.3.9": "enable deterministic training", |
| "0.3.8": "adapt to BundleWorkflow interface", |
| "0.3.7": "add name tag", |
| "0.3.6": "restructure readme to match updated template", |
| "0.3.5": "update metric in metadata", |
| "0.3.4": "add validate.json file and dice score in readme", |
| "0.3.3": "update to use monai 1.0.1", |
| "0.3.2": "enhance readme on commands example", |
| "0.3.1": "fix license Copyright error", |
| "0.3.0": "update license files", |
| "0.2.0": "unify naming", |
| "0.1.0": "complete the model package", |
| "0.0.1": "initialize the model package structure" |
| }, |
| "monai_version": "1.4.0", |
| "pytorch_version": "2.4.0", |
| "numpy_version": "1.24.4", |
| "required_packages_version": { |
| "itk": "5.4.0", |
| "pytorch-ignite": "0.4.11", |
| "scikit-image": "0.23.2", |
| "einops": "0.7.0", |
| "tensorboard": "2.17.0", |
| "nibabel": "5.2.1" |
| }, |
| "supported_apps": {}, |
| "name": "Spleen DeepEdit Interactive Segmentation", |
| "task": "Interactive Spleen Segmentation in CT Images with Point-based Guidance", |
| "description": "An interactive 3D segmentation model that processes 128x128x128 pixel patches from CT scans to segment the spleen. The model incorporates user-provided point annotations through the DeepEdit framework. It accepts positive and negative click inputs to refine segmentation boundaries in real-time.", |
| "authors": "MONAI team", |
| "copyright": "Copyright (c) MONAI Consortium", |
| "data_source": "Task09_Spleen.tar from http://medicaldecathlon.com/", |
| "data_type": "nibabel", |
| "image_classes": "Three channel input: channel 0: CT image scaled to [0, 1], channels 1-2: positive and negative click maps", |
| "label_classes": "Single channel binary mask: 1: spleen, 0: background", |
| "pred_classes": "2 channels OneHot data, channel 1 is spleen, channel 0 is background", |
| "eval_metrics": { |
| "mean_dice": 0.97 |
| }, |
| "intended_use": "This is an example, not to be used for diagnostic purposes", |
| "references": [ |
| "Sakinis, Tomas, et al. 'Interactive segmentation of medical images through fully convolutional neural networks.' arXiv preprint arXiv:1903.08205 (2019)" |
| ], |
| "network_data_format": { |
| "inputs": { |
| "image": { |
| "type": "image", |
| "format": "hounsfield", |
| "modality": "CT", |
| "num_channels": 3, |
| "spatial_shape": [ |
| 128, |
| 128, |
| 128 |
| ], |
| "dtype": "float32", |
| "value_range": [ |
| 0, |
| 1 |
| ], |
| "is_patch_data": false, |
| "channel_def": { |
| "0": "image" |
| } |
| } |
| }, |
| "outputs": { |
| "pred": { |
| "type": "image", |
| "format": "segmentation", |
| "num_channels": 2, |
| "spatial_shape": [ |
| 128, |
| 128, |
| 128 |
| ], |
| "dtype": "float32", |
| "value_range": [ |
| 0, |
| 1 |
| ], |
| "is_patch_data": false, |
| "channel_def": { |
| "0": "background", |
| "1": "spleen" |
| } |
| } |
| } |
| } |
| } |
|
|
