Update total_mr/app.json
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total_mr/app.json
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"short_description": "<b>Description:</b><br>KonfAI-accelerated adaptation of <a href='https://github.com/wasserth/TotalSegmentator'>TotalSegmentator MRI</a>, delivering fast multimodal segmentation of <b>80 major anatomical structures</b> from <b>MRI and CT</b> scans, with significantly reduced inference overhead vs. the original nnU-Net workflow.<br><br><b>How to cite:</b><br><cite>T. Akinci D’Antonoli et al., <i>TotalSegmentator MRI: Robust Sequence-Independent Segmentation of Multiple Anatomic Structures in MRI</i>, Radiology, 2025.</cite>",
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"description": "<b>Description:</b><br>This model integrates TotalSegmentator MRI into the <b>KonfAI</b> inference framework to accelerate deployment in MRI/CT multimodal workflows.<br><br><b>Capabilities:</b><br>• Automatic segmentation of <b>80 major anatomical structures</b> (organs, vessels, skeleton, digestive system)<br>• Robust to <b>sequence variations</b> across scanners, contrasts, acquisition planes, and sites<br>• High-resolution input: <b>1.5 mm isotropic</b><br><br><b>Training data:</b><br>Trained on a highly diverse clinical dataset of <b>1143 scans</b> including <b>616 MRI</b> (30 scanners, 4 sites, many contrast types) and <b>527 CT</b> scans, with expert-validated manual segmentations <br><br><b>How to cite:</b><br><cite>T. Akinci D’Antonoli et al., <i>TotalSegmentator MRI: Robust Sequence-Independent Segmentation of Multiple Anatomic Structures in MRI</i>, Radiology, 2025.</cite>",
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"tta": 0,
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"mc_dropout": 0
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}
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"short_description": "<b>Description:</b><br>KonfAI-accelerated adaptation of <a href='https://github.com/wasserth/TotalSegmentator'>TotalSegmentator MRI</a>, delivering fast multimodal segmentation of <b>80 major anatomical structures</b> from <b>MRI and CT</b> scans, with significantly reduced inference overhead vs. the original nnU-Net workflow.<br><br><b>How to cite:</b><br><cite>T. Akinci D’Antonoli et al., <i>TotalSegmentator MRI: Robust Sequence-Independent Segmentation of Multiple Anatomic Structures in MRI</i>, Radiology, 2025.</cite>",
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"description": "<b>Description:</b><br>This model integrates TotalSegmentator MRI into the <b>KonfAI</b> inference framework to accelerate deployment in MRI/CT multimodal workflows.<br><br><b>Capabilities:</b><br>• Automatic segmentation of <b>80 major anatomical structures</b> (organs, vessels, skeleton, digestive system)<br>• Robust to <b>sequence variations</b> across scanners, contrasts, acquisition planes, and sites<br>• High-resolution input: <b>1.5 mm isotropic</b><br><br><b>Training data:</b><br>Trained on a highly diverse clinical dataset of <b>1143 scans</b> including <b>616 MRI</b> (30 scanners, 4 sites, many contrast types) and <b>527 CT</b> scans, with expert-validated manual segmentations <br><br><b>How to cite:</b><br><cite>T. Akinci D’Antonoli et al., <i>TotalSegmentator MRI: Robust Sequence-Independent Segmentation of Multiple Anatomic Structures in MRI</i>, Radiology, 2025.</cite>",
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"tta": 0,
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"mc_dropout": 0,
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"terminology": {
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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": "pancreas",
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"8": "adrenal_gland_right",
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"9": "adrenal_gland_left",
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"10": "lung_left",
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"11": "lung_right",
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"12": "esophagus",
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"13": "small_bowel",
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"14": "duodenum",
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"15": "colon",
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"16": "urinary_bladder",
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"17": "prostate",
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"18": "sacrum",
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"19": "vertebrae",
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"20": "intervertebral_discs",
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"21": "spinal_cord",
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"22": "heart",
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"23": "aorta",
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"24": "inferior_vena_cava",
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"25": "portal_vein_and_splenic_vein",
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"26": "iliac_artery_left",
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"27": "iliac_artery_right",
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"28": "iliac_vena_left",
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"29": "iliac_vena_right",
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"30": "humerus_left",
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"31": "humerus_right",
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"32": "scapula_left",
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"33": "scapula_right",
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"34": "clavicula_left",
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"35": "clavicula_right",
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"36": "femur_left",
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"37": "femur_right",
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"38": "hip_left",
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"39": "hip_right",
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"40": "gluteus_maximus_left",
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"41": "gluteus_maximus_right",
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"42": "gluteus_medius_left",
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"43": "gluteus_medius_right",
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"44": "gluteus_minimus_left",
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"45": "gluteus_minimus_right",
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"46": "autochthon_left",
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"47": "autochthon_right",
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"48": "iliopsoas_left",
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"49": "iliopsoas_right",
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"50": "brain",
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}
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}
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