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{ |
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"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json", |
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"version": "0.1.9", |
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"changelog": { |
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"0.1.9": "fix the wrong GPU index issue of multi-node", |
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"0.1.8": "Update evalaute doc, GPU usage details, and dataset preparation instructions", |
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"0.1.7": "remove error dollar symbol in readme", |
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"0.1.6": "add RAM usage with CacheDataset and GPU consumtion warning", |
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"0.1.5": "fix mgpu finalize issue", |
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"0.1.4": "Update README Formatting", |
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"0.1.3": "add non-deterministic note", |
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"0.1.2": "Update figure with links", |
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"0.1.1": "adapt to BundleWorkflow interface and val metric", |
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"0.1.0": "complete the model package", |
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"0.0.1": "initialize the model package structure" |
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}, |
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"monai_version": "1.2.0", |
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"pytorch_version": "1.13.1", |
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"numpy_version": "1.22.2", |
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"optional_packages_version": { |
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"nibabel": "4.0.1", |
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"pytorch-ignite": "0.4.9" |
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}, |
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"name": "Whole body CT segmentation", |
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"task": "TotalSegmentator Segmentation", |
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"description": "A pre-trained SegResNet model for volumetric (3D) segmentation of the 104 whole body segments", |
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"authors": "MONAI team", |
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"copyright": "Copyright (c) MONAI Consortium", |
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"data_source": "TotalSegmentator", |
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"data_type": "nibabel", |
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"image_classes": "104 foreground channels, 0 channel for the background, intensity scaled to [0, 1]", |
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"label_classes": "0 is the background, others are whole body segments", |
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"pred_classes": "0 is the background, 104 other chanels are whole body segments", |
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"eval_metrics": { |
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"mean_dice": 0.8 |
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}, |
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"intended_use": "This is an example, not to be used for diagnostic purposes", |
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"references": [ |
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"Wasserthal, J., Meyer, M., Breit, H.C., Cyriac, J., Yang, S. and Segeroth, M., 2022. TotalSegmentator: robust segmentation of 104 anatomical structures in CT images. arXiv preprint arXiv:2208.05868.", |
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"Myronenko, A., Siddiquee, M.M.R., Yang, D., He, Y. and Xu, D., 2022. Automated head and neck tumor segmentation from 3D PET/CT. arXiv preprint arXiv:2209.10809.", |
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"Tang, Y., Gao, R., Lee, H.H., Han, S., Chen, Y., Gao, D., Nath, V., Bermudez, C., Savona, M.R., Abramson, R.G. and Bao, S., 2021. High-resolution 3D abdominal segmentation with random patch network fusion. Medical image analysis, 69, p.101894." |
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], |
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"network_data_format": { |
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"inputs": { |
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"image": { |
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"type": "image", |
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"format": "hounsfield", |
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"modality": "CT", |
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"num_channels": 1, |
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"spatial_shape": [ |
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96, |
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96, |
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96 |
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], |
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"dtype": "float32", |
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"value_range": [ |
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0, |
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1 |
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], |
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"is_patch_data": true, |
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"channel_def": { |
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"0": "image" |
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} |
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} |
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}, |
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"outputs": { |
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"pred": { |
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"type": "image", |
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"format": "segmentation", |
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"num_channels": 105, |
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"spatial_shape": [ |
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96, |
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96, |
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96 |
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], |
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"dtype": "float32", |
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"value_range": [ |
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0, |
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104 |
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], |
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"is_patch_data": true, |
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"channel_def": { |
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"0": "background", |
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"1": "spleen", |
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"2": "kidney_right", |
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"3": "kidney_left", |
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"4": "gallbladder", |
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"5": "liver", |
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"6": "stomach", |
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"7": "aorta", |
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"8": "inferior_vena_cava", |
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"9": "portal_vein_and_splenic_vein", |
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"10": "pancreas", |
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"11": "adrenal_gland_right", |
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"12": "adrenal_gland_left", |
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"13": "lung_upper_lobe_left", |
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"14": "lung_lower_lobe_left", |
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"15": "lung_upper_lobe_right", |
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"16": "lung_middle_lobe_right", |
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"17": "lung_lower_lobe_right", |
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"18": "vertebrae_L5", |
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"19": "vertebrae_L4", |
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"20": "vertebrae_L3", |
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"21": "vertebrae_L2", |
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"22": "vertebrae_L1", |
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"23": "vertebrae_T12", |
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"24": "vertebrae_T11", |
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"25": "vertebrae_T10", |
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"26": "vertebrae_T9", |
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"27": "vertebrae_T8", |
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"28": "vertebrae_T7", |
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"29": "vertebrae_T6", |
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"30": "vertebrae_T5", |
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"31": "vertebrae_T4", |
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"32": "vertebrae_T3", |
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"33": "vertebrae_T2", |
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"34": "vertebrae_T1", |
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"35": "vertebrae_C7", |
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"36": "vertebrae_C6", |
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"37": "vertebrae_C5", |
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"38": "vertebrae_C4", |
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"39": "vertebrae_C3", |
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"40": "vertebrae_C2", |
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"41": "vertebrae_C1", |
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"42": "esophagus", |
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"43": "trachea", |
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"44": "heart_myocardium", |
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"45": "heart_atrium_left", |
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"46": "heart_ventricle_left", |
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"47": "heart_atrium_right", |
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"48": "heart_ventricle_right", |
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"49": "pulmonary_artery", |
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"50": "brain", |
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"51": "iliac_artery_left", |
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"52": "iliac_artery_right", |
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"53": "iliac_vena_left", |
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"54": "iliac_vena_right", |
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"55": "small_bowel", |
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"56": "duodenum", |
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"57": "colon", |
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"58": "rib_left_1", |
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"59": "rib_left_2", |
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"60": "rib_left_3", |
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"61": "rib_left_4", |
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"62": "rib_left_5", |
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"63": "rib_left_6", |
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"64": "rib_left_7", |
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"65": "rib_left_8", |
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"66": "rib_left_9", |
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"67": "rib_left_10", |
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"68": "rib_left_11", |
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"69": "rib_left_12", |
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"70": "rib_right_1", |
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"71": "rib_right_2", |
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"72": "rib_right_3", |
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"73": "rib_right_4", |
|
"74": "rib_right_5", |
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"75": "rib_right_6", |
|
"76": "rib_right_7", |
|
"77": "rib_right_8", |
|
"78": "rib_right_9", |
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"79": "rib_right_10", |
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"80": "rib_right_11", |
|
"81": "rib_right_12", |
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"82": "humerus_left", |
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"83": "humerus_right", |
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"84": "scapula_left", |
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"85": "scapula_right", |
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"86": "clavicula_left", |
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"87": "clavicula_right", |
|
"88": "femur_left", |
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"89": "femur_right", |
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"90": "hip_left", |
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"91": "hip_right", |
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"92": "sacrum", |
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"93": "face", |
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"94": "gluteus_maximus_left", |
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"95": "gluteus_maximus_right", |
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"96": "gluteus_medius_left", |
|
"97": "gluteus_medius_right", |
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"98": "gluteus_minimus_left", |
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"99": "gluteus_minimus_right", |
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"100": "autochthon_left", |
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"101": "autochthon_right", |
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"102": "iliopsoas_left", |
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"103": "iliopsoas_right", |
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"104": "urinary_bladder" |
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} |
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} |
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} |
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} |
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} |
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|