Update total/app.json

total/app.json

@@ -4,6 +4,36 @@
     "description": "<b>Description:</b><br>This model is an optimized adaptation of the original <a href='https://github.com/wasserth/TotalSegmentator'>TotalSegmentator</a> for the <b>KonfAI</b> deep learning framework.<br><br><b>Capabilities:</b><br>• Segmentation of <b>118 anatomical classes</b> covering organs, bones, muscles, and vessels<br>• Enhanced runtime and memory efficiency vs. the original nnU-Net implementation<br>• High-resolution input: <b>1.5 mm isotropic</b><br><br><b>Training data:</b><br>Trained on a diverse dataset of <b>1204 whole-body CT examinations</b> including different scanners, acquisition settings, contrast phases, and major pathologies (27 organs, 59 bones, 10 muscles, 8 vessels), with manual expert-reviewed 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>",
     "tta": 0,
     "mc_dropout": 0,
+    "inputs": {
+      "Volume": {
+        "display_name": "Input Volume",
+        "volume_type": "VOLUME",
+        "required": true
+      }
+    },
+    "outputs": {
+      "Segmentation": {
+        "display_name": "Segmentation",
+        "volume_type": "SEGMENTATION",
+        "required": true
+      }
+    },
+    "inputs_evaluations": {
+      "Image": {
+        "Evaluation.yml": {
+          "Segmentation": {
+            "display_name": "Output Segmentation",
+            "volume_type": "VOLUME",
+            "required": true
+          },
+          "GT_Segmentation": {
+            "display_name": "GT Segmentation",
+            "volume_type": "VOLUME",
+            "required": true
+          }
+        }
+      }
+    },
     "terminology": {
       "1": { "name": "spleen", "color": "#4B79EA" },
       "2": { "name": "kidney_right", "color": "#A8EA4B" },