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  "extra_authors": [
            
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    {
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    {
            
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      "extra_author": "Shoji Kido",
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      "extra_author": "Shoji Kido",
            
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      "description": "",
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      "description": "",
            
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      "name": "medical-image-segmentation",
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      "name": "medical-image-segmentation",
            
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      "title": "Medical Image Segmentation"
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      "title": "Medical Image Segmentation"
            
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  "name": 
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  "name": 
            
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abdominal-multi-organ-segmentation-2022--amos2022--challenge-dataset",
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abdominal-multi-organ-segmentation-2022--amos2022--challenge-dataset",
            
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  "notes": "The Abdominal Multi Organ Segmentation 2022 (AMOS2022) 
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  "notes": "The Abdominal Multi Organ Segmentation 2022 (AMOS2022) 
            
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challenge dataset contains 500 CT and 100 MRI scans collected from 
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challenge dataset contains 500 CT and 100 MRI scans collected from 
            
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multiple sites, a wide range of imaging conditions, and patient 
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multiple sites, a wide range of imaging conditions, and patient 
            
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backgrounds with 15 voxel-level annotations.",
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backgrounds with 15 voxel-level annotations.",
            
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      "display_name": "Medical Image Segmentation",
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      "display_name": "Medical Image Segmentation",
            
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      "name": "Medical Image Segmentation",
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  "title": "Abdominal Multi Organ Segmentation 2022 (AMOS2022) 
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  "title": "Abdominal Multi Organ Segmentation 2022 (AMOS2022) 
            
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challenge dataset",
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challenge dataset",
            
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}