LesionSegmenter: surface all four lesions + upload-time selector

PanTS-Demo/src/helpers/constants.ts

@@ -79,6 +79,9 @@ export const segmentation_category_colors: { [key: number]: Color } = {
 	30: [100, 149, 237, 254], // Renal vein left (cornflower blue)
 	31: [70, 130, 180, 254],  // Renal vein right (steel blue)
 	32: [192, 192, 192, 254], // CBD stent (silver-gray)
+	33: [255, 140, 0, 254],   // Liver lesion (dark orange)
+	34: [255, 215, 0, 254],   // Kidney lesion (gold)
+	35: [220, 20, 60, 254],   // Colon lesion (crimson)
 };
 
 // Rotating palette of colours to hand out to new classes.
@@ -128,6 +131,9 @@ export const segmentation_categories: SegmentationCategories[] = [
 	"renal_vein_left",
 	"renal_vein_right",
 	"cbd_stent",
+	"liver_lesion",
+	"kidney_lesion",
+	"colon_lesion",
 ];
 
 export const OrganSystemsArray: Systems[] = [
@@ -168,7 +174,7 @@ export const OrganSystems: OrganSystemsType = {
 		"renal_vein_right",
 	],
 	"Endocrine System": ["adrenal_gland_left", "adrenal_gland_right"],
-	"Urinary System": [{ Kidneys: ["kidney_left", "kidney_right"] }, "bladder"],
+	"Urinary System": [{ Kidneys: ["kidney_left", "kidney_right", "kidney_lesion"] }, "bladder"],
 	// bladder
 	"Skeletal System": ["femur_left", "femur_right"],
 
@@ -184,10 +190,12 @@ export const OrganSystems: OrganSystemsType = {
 			],
 		},
 		"colon",
+		"colon_lesion",
 		"duodenum",
 		"intestine",
 		"stomach",
 		"liver",
+		"liver_lesion",
 		"common_bile_duct",
 		"gall_bladder",
 		"cbd_stent",

PanTS-Demo/src/routes/UploadPage.css

@@ -1157,3 +1157,23 @@
   background: rgba(0, 0, 0, 0.05);
   border-color: rgba(0, 0, 0, 0.2);
 }
+
+/* LesionSegmenter lesion-target sub-selector (appears under Model when
+   LesionSegmenter is chosen). Reuses .model-dropdown-btn for the select. */
+.lesion-target-select {
+  display: flex;
+  align-items: center;
+  gap: 8px;
+  margin-top: 8px;
+}
+.lesion-target-label {
+  font-size: 11px;
+  font-weight: 600;
+  color: rgba(0, 0, 0, 0.6);
+  text-transform: uppercase;
+  letter-spacing: 0.04em;
+}
+.lesion-target-select select.model-dropdown-btn {
+  flex: 1;
+  cursor: pointer;
+}

PanTS-Demo/src/routes/UploadPage.tsx

@@ -165,6 +165,12 @@ const UploadPage: React.FC = () => {
     | ""
   >("None");
   const [modelDropOpen, setModelDropOpen] = useState(false);
+  // LesionSegmenter computes liver/pancreatic/kidney/colon lesions in one pass;
+  // this selects which lesion to feature. Only pancreatic is GT-validated; the
+  // other three are surfaced as experimental.
+  const [lesionTarget, setLesionTarget] = useState<
+    "pancreatic" | "liver" | "kidney" | "colon"
+  >("pancreatic");
   const modelDropRef = useRef<HTMLDivElement>(null);
   const [preDropOpen, setPreDropOpen] = useState(false);
   const preDropRef = useRef<HTMLDivElement>(null);
@@ -571,6 +577,9 @@ const UploadPage: React.FC = () => {
       inferFd.append("session_id", sid);
       inferFd.append("model_name", model);
       inferFd.append("uploaded_filename", uploadedName);
+      if (model === "LesionSegmenter") {
+        inferFd.append("lesion_target", lesionTarget);
+      }
       const res = await fetch(`${API_BASE}/api/run-epai-inference`, {
         method: "POST",
         body: inferFd,
@@ -1413,6 +1422,31 @@ const UploadPage: React.FC = () => {
                   </div>
                 )}
               </div>
+              {selectedModel === "LesionSegmenter" && (
+                <div className="lesion-target-select">
+                  <label
+                    htmlFor="lesion-target"
+                    className="lesion-target-label"
+                  >
+                    Lesion
+                  </label>
+                  <select
+                    id="lesion-target"
+                    className="model-dropdown-btn"
+                    value={lesionTarget}
+                    onChange={(e) =>
+                      setLesionTarget(
+                        e.target.value as typeof lesionTarget
+                      )
+                    }
+                  >
+                    <option value="pancreatic">Pancreatic lesion</option>
+                    <option value="liver">Liver lesion (experimental)</option>
+                    <option value="kidney">Kidney lesion (experimental)</option>
+                    <option value="colon">Colon lesion (experimental)</option>
+                  </select>
+                </div>
+              )}
             </div>
 
             <div className="pipeline-arrow">→</div>

PanTS-Demo/src/types.tsx

@@ -122,7 +122,10 @@ export type SegmentationCategories =
 	| "intestine"
 	| "renal_vein_left"
 	| "renal_vein_right"
-	| "cbd_stent";
+	| "cbd_stent"
+	| "liver_lesion"
+	| "kidney_lesion"
+	| "colon_lesion";
 
 export type OrganMeshInfo = {
   id: number;

flask-server/services/auto_segmentor.py

@@ -206,6 +206,8 @@ def run_auto_segmentation(input_path, session_dir, model, session_id=None, on_st
     "superior_mesenteric_artery": 27, "veins": 28,
     # extended labels for full ePAI output
     "intestine": 29, "renal_vein_left": 30, "renal_vein_right": 31, "cbd_stent": 32,
+    # LesionSegmenter extra lesion classes (pancreatic_lesion already at 22)
+    "liver_lesion": 33, "kidney_lesion": 34, "colon_lesion": 35,
 }
 
 # ePAI model label → viewer label (all 25 classes from dataset.json)
@@ -295,9 +297,12 @@ def run_auto_segmentation(input_path, session_dir, model, session_id=None, on_st
 # NOT mapped (no viewer category exists yet, left as background rather than
 # guessing at a slot and risking a mislabeled structure): esophagus, rectum,
 # vertebrae_* (10 classes), trachea, heart, hip_left, hip_right, sacrum,
-# uterus, liver_lesion, kidney_lesion, colon_lesion. pancreatic_lesion is the
-# one this model exists to add and maps onto the same viewer slot ePAI and
-# Atlas-Net already use for their own PDAC/cyst/PNET subtypes.
+# uterus. pancreatic_lesion maps onto the same viewer slot ePAI and Atlas-Net
+# use for their PDAC/cyst/PNET subtypes. liver_lesion/kidney_lesion/colon_lesion
+# get their own viewer slots (33/34/35) -- this single model already computes all
+# four lesions in one forward pass, so surfacing the other three is free at
+# runtime. NOTE: only pancreatic_lesion has ground-truth validation on PanTS;
+# the other three are surfaced but flagged experimental in the UI.
 _LESIONSEG_TO_VIEWER = {
     1: _VIEWER_LABELS["aorta"],
     2: _VIEWER_LABELS["gall_bladder"],
@@ -319,7 +324,10 @@ def run_auto_segmentation(input_path, session_dir, model, session_id=None, on_st
     19: _VIEWER_LABELS["prostate"],
     21: _VIEWER_LABELS["lung_left"],
     22: _VIEWER_LABELS["lung_right"],
+    39: _VIEWER_LABELS["liver_lesion"],
     40: _VIEWER_LABELS["pancreatic_lesion"],
+    41: _VIEWER_LABELS["kidney_lesion"],
+    42: _VIEWER_LABELS["colon_lesion"],
 }