| { | |
| "schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20240725.json", | |
| "version": "0.2.3", | |
| "changelog": { | |
| "0.2.3": "enhance metadata with improved descriptions", | |
| "0.2.2": "update to huggingface hosting", | |
| "0.2.1": "update issue for IgniteInfo", | |
| "0.2.0": "use monai 1.4 and update large files", | |
| "0.1.9": "update to use monai 1.3.1", | |
| "0.1.8": "add load_pretrain flag for infer", | |
| "0.1.7": "add checkpoint loader for infer", | |
| "0.1.6": "set image_only to False", | |
| "0.1.5": "add support for TensorRT conversion and inference", | |
| "0.1.4": "fix the wrong GPU index issue of multi-node", | |
| "0.1.3": "remove error dollar symbol in readme", | |
| "0.1.2": "add RAM usage with CachDataset", | |
| "0.1.1": "deterministic retrain benchmark and add link", | |
| "0.1.0": "fix mgpu finalize issue", | |
| "0.0.9": "Update README Formatting", | |
| "0.0.8": "enable deterministic training", | |
| "0.0.7": "Update with figure links", | |
| "0.0.6": "adapt to BundleWorkflow interface", | |
| "0.0.5": "add name tag", | |
| "0.0.4": "Fix evaluation", | |
| "0.0.3": "Update to use MONAI 1.1.0", | |
| "0.0.2": "Update The Torch Vision Transform", | |
| "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": { | |
| "nibabel": "5.2.1", | |
| "pytorch-ignite": "0.4.11", | |
| "torchvision": "0.19.0", | |
| "scipy": "1.13.1", | |
| "scikit-image": "0.23.2", | |
| "tensorboard": "2.17.0" | |
| }, | |
| "supported_apps": {}, | |
| "name": "Pathology NuClick Annotation", | |
| "task": "Interactive Nuclei Segmentation in Histopathology Images", | |
| "description": "An interactive nuclei segmentation model based on the NuClick framework. The model processes 128x128 pixel RGB images with positive and negative click signals to generate nuclei segmentation masks. Trained on the CoNSeP dataset", | |
| "authors": "MONAI team", | |
| "copyright": "Copyright (c) MONAI Consortium", | |
| "data_source": "consep_dataset.zip from https://warwick.ac.uk/fac/cross_fac/tia/data/hovernet", | |
| "data_type": "png", | |
| "image_classes": "RGB channel data, intensity scaled to [0, 1]", | |
| "label_classes": "single channel data", | |
| "pred_classes": "1 channel data, with value 1 as nuclei and 0 as background", | |
| "eval_metrics": { | |
| "mean_dice": 0.85 | |
| }, | |
| "intended_use": "This is an example, not to be used for diagnostic purposes", | |
| "references": [ | |
| "Koohbanani, Navid Alemi, et al. \"NuClick: A Deep Learning Framework for Interactive Segmentation of Microscopy Images.\" https://arxiv.org/abs/2005.14511", | |
| "S. Graham, Q. D. Vu, S. E. A. Raza, A. Azam, Y-W. Tsang, J. T. Kwak and N. Rajpoot. \"HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images.\" Medical Image Analysis, Sept. 2019. https://doi.org/10.1016/j.media.2019.101563", | |
| "NuClick PyTorch Implementation, https://github.com/mostafajahanifar/nuclick_torch" | |
| ], | |
| "network_data_format": { | |
| "inputs": { | |
| "image": { | |
| "type": "png", | |
| "format": "RGB", | |
| "modality": "regular", | |
| "num_channels": 5, | |
| "spatial_shape": [ | |
| 128, | |
| 128 | |
| ], | |
| "dtype": "float32", | |
| "value_range": [ | |
| 0, | |
| 1 | |
| ], | |
| "is_patch_data": false, | |
| "channel_def": { | |
| "0": "R", | |
| "1": "G", | |
| "2": "B", | |
| "3": "+ve Signal", | |
| "4": "-ve Signal" | |
| } | |
| } | |
| }, | |
| "outputs": { | |
| "pred": { | |
| "type": "image", | |
| "format": "segmentation", | |
| "num_channels": 1, | |
| "spatial_shape": [ | |
| 128, | |
| 128 | |
| ], | |
| "dtype": "float32", | |
| "value_range": [ | |
| 0, | |
| 1 | |
| ], | |
| "is_patch_data": false, | |
| "channel_def": { | |
| "0": "Nuclei" | |
| } | |
| } | |
| } | |
| } | |
| } | |