Update total_mr/metadata.json

total_mr/metadata.json

@@ -1,7 +1,7 @@
 {
     "display_name": "TotalSegmentator MRI",
     "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>",
-    "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., Radiology, 2025.</cite>",
+    "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>",
     "tta": 0,
     "mc_dropout": 0
 }