Update total-3mm/app.json
Browse files- total-3mm/app.json +120 -1
total-3mm/app.json
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"short_description": "<b>Description:</b><br>Lightweight KonfAI adaptation of <a href='https://github.com/wasserth/TotalSegmentator'>TotalSegmentator</a> trained at <b>3 mm resolution</b>, reducing GPU/RAM requirements while segmenting <b>118 anatomical structures</b> in whole-body CT.<br><br><b>How to cite:</b><br><cite>J. Wasserthal et al., <i>TotalSegmentator: Robust Segmentation of 104 Anatomical Structures in CT Images</i>, Radiology: AI, 2023.</cite>",
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"description": "<b>Description:</b><br>KonfAI-optimized version of the original nnU-Net-based TotalSegmentator 3 mm model.<br><br><b>Capabilities:</b><br>• Whole-body CT segmentation of <b>118 structures</b> (organs, bones, muscles, vessels)<br>• Reduced computational footprint for lower memory and faster throughput<br>• <b>3 mm isotropic</b> inference for easier deployment on large datasets<br><br><b>Training data:</b><br>Trained on <b>1204 clinically-derived CT scans</b> with strong diversity in contrast phases, scanner types and pathologies, with expert-reviewed manual annotations<br><br><b>How to cite:</b><br><cite>J. Wasserthal et al., <i>TotalSegmentator: Robust Segmentation of 104 Anatomical Structures in CT Images</i>, Radiology: AI, 2023.</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>Lightweight KonfAI adaptation of <a href='https://github.com/wasserth/TotalSegmentator'>TotalSegmentator</a> trained at <b>3 mm resolution</b>, reducing GPU/RAM requirements while segmenting <b>118 anatomical structures</b> in whole-body CT.<br><br><b>How to cite:</b><br><cite>J. Wasserthal et al., <i>TotalSegmentator: Robust Segmentation of 104 Anatomical Structures in CT Images</i>, Radiology: AI, 2023.</cite>",
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"description": "<b>Description:</b><br>KonfAI-optimized version of the original nnU-Net-based TotalSegmentator 3 mm model.<br><br><b>Capabilities:</b><br>• Whole-body CT segmentation of <b>118 structures</b> (organs, bones, muscles, vessels)<br>• Reduced computational footprint for lower memory and faster throughput<br>• <b>3 mm isotropic</b> inference for easier deployment on large datasets<br><br><b>Training data:</b><br>Trained on <b>1204 clinically-derived CT scans</b> with strong diversity in contrast phases, scanner types and pathologies, with expert-reviewed manual annotations<br><br><b>How to cite:</b><br><cite>J. Wasserthal et al., <i>TotalSegmentator: Robust Segmentation of 104 Anatomical Structures in CT Images</i>, Radiology: AI, 2023.</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_upper_lobe_left",
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"11": "lung_lower_lobe_left",
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"12": "lung_upper_lobe_right",
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"13": "lung_middle_lobe_right",
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"14": "lung_lower_lobe_right",
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"15": "esophagus",
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"16": "trachea",
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"17": "thyroid_gland",
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"18": "small_bowel",
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"19": "duodenum",
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"20": "colon",
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"21": "urinary_bladder",
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"22": "prostate",
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"23": "kidney_cyst_left",
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"24": "kidney_cyst_right",
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"25": "sacrum",
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"26": "vertebrae_S1",
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"27": "vertebrae_L5",
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"28": "vertebrae_L4",
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"29": "vertebrae_L3",
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"30": "vertebrae_L2",
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"31": "vertebrae_L1",
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"32": "vertebrae_T12",
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"33": "vertebrae_T11",
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"34": "vertebrae_T10",
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"35": "vertebrae_T9",
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"36": "vertebrae_T8",
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"37": "vertebrae_T7",
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"38": "vertebrae_T6",
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"39": "vertebrae_T5",
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"40": "vertebrae_T4",
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"41": "vertebrae_T3",
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"42": "vertebrae_T2",
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"43": "vertebrae_T1",
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"44": "vertebrae_C7",
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"45": "vertebrae_C6",
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"46": "vertebrae_C5",
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"47": "vertebrae_C4",
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"48": "vertebrae_C3",
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"49": "vertebrae_C2",
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"50": "vertebrae_C1",
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"51": "heart",
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"52": "aorta",
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"53": "pulmonary_vein",
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"54": "brachiocephalic_trunk",
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"55": "subclavian_artery_right",
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"56": "subclavian_artery_left",
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"57": "common_carotid_artery_right",
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"58": "common_carotid_artery_left",
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"59": "brachiocephalic_vein_left",
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"60": "brachiocephalic_vein_right",
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"61": "atrial_appendage_left",
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"62": "superior_vena_cava",
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"63": "inferior_vena_cava",
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"64": "portal_vein_and_splenic_vein",
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"65": "iliac_artery_left",
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"66": "iliac_artery_right",
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"67": "iliac_vena_left",
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"68": "iliac_vena_right",
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"69": "humerus_left",
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"70": "humerus_right",
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"71": "scapula_left",
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"72": "scapula_right",
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"73": "clavicula_left",
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"74": "clavicula_right",
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"75": "femur_left",
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"76": "femur_right",
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"77": "hip_left",
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"78": "hip_right",
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"79": "spinal_cord",
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"80": "gluteus_maximus_left",
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"81": "gluteus_maximus_right",
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"82": "gluteus_medius_left",
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"83": "gluteus_medius_right",
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"84": "gluteus_minimus_left",
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"85": "gluteus_minimus_right",
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"86": "autochthon_left",
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"87": "autochthon_right",
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"88": "iliopsoas_left",
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"89": "iliopsoas_right",
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"90": "brain",
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"91": "skull",
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"92": "rib_left_1",
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"93": "rib_left_2",
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"94": "rib_left_3",
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"95": "rib_left_4",
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"96": "rib_left_5",
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"97": "rib_left_6",
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"98": "rib_left_7",
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"99": "rib_left_8",
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"100": "rib_left_9",
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"101": "rib_left_10",
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"102": "rib_left_11",
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"103": "rib_left_12",
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"104": "rib_right_1",
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"105": "rib_right_2",
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"106": "rib_right_3",
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"107": "rib_right_4",
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"108": "rib_right_5",
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"109": "rib_right_6",
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"110": "rib_right_7",
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"111": "rib_right_8",
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"112": "rib_right_9",
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"113": "rib_right_10",
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"114": "rib_right_11",
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"115": "rib_right_12",
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"116": "sternum",
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"117": "costal_cartilages"
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}
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}
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