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Update total_mr-3mm/app.json

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  1. total_mr-3mm/app.json +1 -0
total_mr-3mm/app.json CHANGED
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  "description": "<b>Description:</b><br>This model integrates the reduced-resolution MRI-3mm configuration of TotalSegmentator into the <b>KonfAI</b> accelerated inference pipeline for efficient MRI/CT deployment.<br><br><b>Capabilities:</b><br>• Segmentation of <b>50 essential anatomical structures</b> (major organs, key bones, large vessels)<br>• <b>3 mm</b> isotropic input for high-throughput processing and lower GPU requirements<br>• Robust to acquisition variability including scanner type, contrast, and sequence parameters<br><br><b>Training data:</b><br>Trained on a diverse cohort of <b>1143 clinical scans</b> including <b>616 MRI</b> (multi-site, multi-scanner, multi-sequence) and <b>527 CT</b>, with expert-validated reference masks<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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  "inputs": {
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  "Volume": {
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  "display_name": "Input Volume",
 
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  "description": "<b>Description:</b><br>This model integrates the reduced-resolution MRI-3mm configuration of TotalSegmentator into the <b>KonfAI</b> accelerated inference pipeline for efficient MRI/CT deployment.<br><br><b>Capabilities:</b><br>• Segmentation of <b>50 essential anatomical structures</b> (major organs, key bones, large vessels)<br>• <b>3 mm</b> isotropic input for high-throughput processing and lower GPU requirements<br>• Robust to acquisition variability including scanner type, contrast, and sequence parameters<br><br><b>Training data:</b><br>Trained on a diverse cohort of <b>1143 clinical scans</b> including <b>616 MRI</b> (multi-site, multi-scanner, multi-sequence) and <b>527 CT</b>, with expert-validated reference masks<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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+ "models": ["M852.pt"],
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  "inputs": {
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  "Volume": {
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  "display_name": "Input Volume",