Upload folder using huggingface_hub

main.py

@@ -551,110 +551,12 @@ oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")
 # =========================================================================
 # MEDICAL DOMAINS CONFIGURATION
 # =========================================================================
-MEDICAL_DOMAINS = {
-    'Thoracic': {
-        'domain_prompt': 'Chest X-Ray Analysis',
-        'specific_labels': [
-            'Diffuse interstitial opacities or ground-glass pattern (Viral/Atypical Pneumonia)',
-            'Focal alveolar consolidation with air bronchograms (Bacterial Pneumonia)',
-            'Normal chest radiograph: normal cardiothoracic ratio, clear lungs, no pleural abnormality', 
-            'Pneumothorax (Lung collapse)',
-            'Pleural Effusion (Fluid)',
-            'Cardiomegaly with clear lung fields (no pulmonary edema)', 
-            'Cardiomegaly with pulmonary congestion or edema',
-            'Pulmonary Edema (without cardiomegaly)',
-            'Lung Nodule or Mass',
-            'Atelectasis (Lung collapse)'
-        ],
-        'logic_gate': { # Renamed from morphology_check
-            'prompt': 'Evaluate cardiac silhouette size',
-            'labels': ['Normal cardiac size (CTR < 0.5)', 'Enlarged cardiac silhouette (Cardiomegaly)'],
-            'penalty_target': 'Normal' # If abnormal, penalize this label
-        }
-    },
-    'Dermatology': {
-        'domain_prompt': 'Dermatoscopic analysis of a pigmented or non-pigmented skin lesion',
-        'specific_labels': [
-            'Normal skin without visible lesion or abnormal pigmentation',
-            'Benign melanocytic nevus with symmetry and uniform pigmentation',
-            'Seborrheic keratosis (benign warty lesion)',
-            'Malignant melanoma with asymmetry, irregular borders, and color variegation',
-            'Basal cell carcinoma (pearly or ulcerated lesion)',
-            'Squamous cell carcinoma (crusty or budding lesion)',
-            'Inflammatory skin lesion (Eczema, Psoriasis)'
-        ],
-        'logic_gate': {
-            'prompt': 'Is there a visible skin lesion?',
-            'labels': ['No visible skin lesion', 'Visible skin lesion (pigmented or non-pigmented)'],
-            'penalty_target': 'ALL_PATHOLOGY', # Special flag
-            'abnormal_index': 0 # "No visible lesion" is the blocker here (index 0)
-        }
-    },
-    'Histology': {
-        'domain_prompt': 'Microscopic analysis of a histological section (H&E stain)',
-        'specific_labels': [
-            'Healthy breast tissue with preserved lobular architecture',
-            'Healthy prostatic tissue with regular glands',
-            'Invasive ductal carcinoma (Disorganized cells)',
-            'Prostate adenocarcinoma (Gland fusion)',
-            'Cervical dysplasia or intraepithelial neoplasia',
-            'Colon cancer tumor tissue',
-            'Lung cancer tumor tissue',
-            'Adipose tissue (Fat) or connective stroma',
-            'Preparation artifact, empty area, or blurred region' # Explicit Label
-        ],
-        'logic_gate': {
-            'prompt': 'Assess histological validity of the image',
-            'labels': ['Adequate H&E tissue section', 'Artifact, empty area, or blurred region'],
-            'penalty_target': 'ALL_DIAGNOSIS',
-            'abnormal_index': 1 # "Artifact" is the blocker
-        }
-    },
-    'Ophthalmology': {
-        'domain_prompt': 'Fundus photography (Retina)',
-        'specific_labels': [
-            'Normal retina with visible optic disc and macula',
-            'Diabetic retinopathy (hemorrhages, exudates)',
-            'Glaucoma (optic disc cupping)',
-            'Macular degeneration (drusen or atrophy)'
-        ],
-        'logic_gate': {
-             'prompt': 'Is the fundus image clinically interpretable?',
-             'labels': ['Good quality fundus image', 'Poor quality, uninterpretable or partial view'],
-             'penalty_target': 'ALL_DIAGNOSIS',
-             'abnormal_index': 1 # "Poor quality" is the blocker
-        }
-    },
-    'Orthopedics': {
-        'domain_prompt': 'Bone X-Ray (Musculoskeletal)',
-        'stage_1_triage': {
-            'prompt': 'Anatomical region identification',
-            'labels': [
-                'Other x-ray view (Chest, Hand, Foot, Pediatric) - OUT OF DISTRIBUTION',
-                'A knee x-ray view (Knee Joint)'
-            ]
-        },
-        'specific_labels': [ # Fallback if stage 2 fails or logic changes
-             'Severe osteoarthritis (Grade 4)', 'Moderate osteoarthritis (Grade 2-3)', 'Normal knee', 'Implant'
-        ],
-        'stage_2_diagnosis': {
-            'prompt': 'Knee Osteoarthritis Severity Assessment',
-            'labels': [
-                'Severe osteoarthritis with bone-on-bone contact (Grade 4)',
-                'Moderate osteoarthritis with definite joint space narrowing (Grade 2-3)',
-                'Normal knee joint with preserved joint space (Grade 0-1)',
-                'Total knee arthroplasty (TKA) with metallic implant', # Label included
-                'Acute knee fracture or dislocation'
-            ]
-        },
-        'logic_gate': {
-            'prompt': 'Is there a metallic implant?',
-            'labels': ['Native knee joint', 'Knee with metallic implant (Arthroplasty)'],
-            'penalty_target': 'Osteoarthritis', # Can't have OA if implant
-            'abnormal_index': 1
-        }
-    }
-}
+from medical_labels import MEDICAL_DOMAINS, LABEL_TRANSLATIONS_FR, DOMAIN_TRANSLATIONS_FR
+
+# =========================================================================
+# PYDANTIC MODELS
+# =========================================================================
+class JobStatus(str, Enum):
 
 # =========================================================================
 # PYDANTIC MODELS
@@ -843,7 +745,7 @@ class MedSigClipWrapper:
 
     def predict(self, image_bytes: bytes, username: str = None) -> Dict[str, Any]:
         """Run hierarchical inference using SigLIP Zero-Shot."""
-        # ... (rest of function until line 1094) ...
+    # ... (rest of function until line 1094) ...
         # I need to match the indentation and context. 
         # Since I can't see "inside" the dots in a replace, I have to be careful.
         # It's better to update just the definition line and the call to enhance_analysis_result.
@@ -863,6 +765,47 @@ class MedSigClipWrapper:
             import torch
             import pydicom
 
+            # ========================================================
+            # LOCALIZATION HELPER
+            # ========================================================
+            def localize_result(result_json: Dict[str, Any]) -> Dict[str, Any]:
+                """
+                Translate the analysis result to French using Canonical IDs.
+                This allows the Model to run in English and the UI to display in French.
+                """
+                localized = result_json.copy()
+                
+                # 1. Translate Domain
+                domain_key = localized.get('domain', {}).get('label')
+                if domain_key in DOMAIN_TRANSLATIONS_FR:
+                    localized['domain']['label_fr'] = DOMAIN_TRANSLATIONS_FR[domain_key]
+                    localized['domain']['label'] = DOMAIN_TRANSLATIONS_FR[domain_key] # Override for simple UI
+                
+                # 2. Translate Specific Results
+                if 'specific' in localized:
+                    new_specific = []
+                    for item in localized['specific']:
+                        label_id = item.get('label_id')
+                        translation = LABEL_TRANSLATIONS_FR.get(label_id)
+                        
+                        if translation:
+                            new_item = item.copy()
+                            new_item['label'] = translation['short'] # Use Short Title for UI
+                            new_item['description'] = translation['long'] # Use Long Description
+                            new_item['severity'] = translation.get('severity', 'medium')
+                            new_specific.append(new_item)
+                        else:
+                            # Fallback if ID missing (should not happen in strict mode)
+                            new_specific.append(item)
+                    
+                    localized['specific'] = new_specific
+                
+                # 3. Handle QC failure case (already localized manually in rejection_result)
+                if 'diagnosis' in localized and "Analyse Refusée" in localized['diagnosis']:
+                     pass # Already localized string
+                
+                return localized
+
             # Image preprocessing functions
             def process_dicom(file_bytes: bytes) -> Tuple[Image.Image, Dict[str, Any]]:
                 """Convert DICOM bytes to PIL Image with tags."""
@@ -1034,10 +977,12 @@ class MedSigClipWrapper:
                     logger.info("Triage indicates Normal/Healthy. Skipping Stage 2.")
             else:
                 # Flat Mode (Thoracic, Dermato, etc.)
-                specific_labels_raw = domain_config['specific_labels']
+                specific_items = domain_config['specific_labels']
+                # Extract text prompts for CLIP
+                labels_en = [item['label_en'] for item in specific_items]
                 
                 inputs_specific = self.processor(
-                    text=specific_labels_raw, 
+                    text=labels_en, 
                     images=image, 
                     padding="max_length", 
                     return_tensors="pt"
@@ -1048,9 +993,10 @@ class MedSigClipWrapper:
                 
                 probs_specific = torch.softmax(outputs_specific.logits_per_image, dim=1)[0]
                 
-                for i, label in enumerate(specific_labels_raw):
+                for i, item in enumerate(specific_items):
                     specific_results.append({
-                        "label": label,
+                        "label_id": item['id'],
+                        "label": item['label_en'], # Keep EN for internal logic
                         "probability": round(float(probs_specific[i] * 100), 2)
                     })
             
@@ -1062,11 +1008,11 @@ class MedSigClipWrapper:
                  
                  for res in specific_results:
                       should_penalize = False
-                      label_text = res['label']
+                      label_text = res['label'] # English text
+                      label_id = res['label_id']
                       
                       if logic_penalty_target == 'ALL_DIAGNOSIS':
                           # Penalize EVERYTHING (e.g. Poor Quality Image)
-                          # Except the specific label that describes the failure (e.g. "Preparation artifact")
                           # Heuristic: If label contains "Artifact" or "Quality" or "Partial", don't penalize.
                           if "Artifact" in label_text or "Quality" in label_text or "Partial" in label_text or "Empty" in label_text:
                               pass 
@@ -1075,14 +1021,15 @@ class MedSigClipWrapper:
 
                       elif logic_penalty_target == 'ALL_PATHOLOGY':
                           # Penalize if it implies pathology (i.e., NOT Normal/Healthy/Benign/Non-specific)
-                          # Safe approach: If it's NOT explicitly "Normal", "Healthy", "Non-specific", penalize it.
                           is_benign = "Normal" in label_text or "Healthy" in label_text or "Non-specific" in label_text or "Benign" in label_text
                           if not is_benign:
                               should_penalize = True
                               
                       else:
-                          # String Match Target (e.g. "Normal", "Osteoarthritis")
-                          if logic_penalty_target in label_text:
+                          # ID Match (Canonical) OR String Match (Fallback)
+                          if logic_penalty_target == label_id:
+                              should_penalize = True
+                          elif logic_penalty_target in label_text:
                               should_penalize = True
                       
                       if should_penalize:

medical_labels.py

@@ -0,0 +1,307 @@
+from typing import Dict, List, Any
+
+# =========================================================================
+# CANONICAL MEDICAL DOMAINS CONFIGURATION (MODEL SOURCE OF TRUTH)
+# =========================================================================
+# - Prompts must be in ENGLISH (Model Language).
+# - Labels must have a stable 'id'.
+# - Logic Gates define structural/quality constraints.
+
+MEDICAL_DOMAINS = {
+    'Thoracic': {
+        'id': 'DOM_THORACIC',
+        'domain_prompt': 'Chest X-Ray Analysis',
+        'specific_labels': [
+            {'id': 'TH_PNEUMONIA_VIRAL', 'label_en': 'Diffuse interstitial opacities or ground-glass pattern (Viral/Atypical Pneumonia)'},
+            {'id': 'TH_PNEUMONIA_BACT', 'label_en': 'Focal alveolar consolidation with air bronchograms (Bacterial Pneumonia)'},
+            {'id': 'TH_NORMAL', 'label_en': 'Normal chest radiograph: normal cardiothoracic ratio, clear lungs, no pleural abnormality'}, 
+            {'id': 'TH_PNEUMOTHORAX', 'label_en': 'Pneumothorax (Lung collapse)'},
+            {'id': 'TH_PLEURAL_EFFUSION', 'label_en': 'Pleural Effusion (Fluid)'},
+            {'id': 'TH_CARDIOMEGALY', 'label_en': 'Cardiomegaly with clear lung fields (no pulmonary edema)'}, 
+            {'id': 'TH_CARDIOMEGALY_EDEMA', 'label_en': 'Cardiomegaly with pulmonary congestion or edema'},
+            {'id': 'TH_EDEMA', 'label_en': 'Pulmonary Edema (without cardiomegaly)'},
+            {'id': 'TH_NODULE', 'label_en': 'Lung Nodule or Mass'},
+            {'id': 'TH_ATELECTASIS', 'label_en': 'Atelectasis (Lung collapse)'}
+        ],
+        'logic_gate': {
+            'prompt': 'Evaluate cardiac silhouette size',
+            'labels': ['Normal cardiac size (CTR < 0.5)', 'Enlarged cardiac silhouette (Cardiomegaly)'],
+            'penalty_target': 'TH_NORMAL', # Penalize the ID of the normal label
+            'abnormal_index': 1
+        }
+    },
+    'Dermatology': {
+        'id': 'DOM_DERMATOLOGY',
+        'domain_prompt': 'Dermatoscopic analysis of a pigmented or non-pigmented skin lesion',
+        'specific_labels': [
+            {'id': 'DERM_NORMAL', 'label_en': 'Normal skin without visible lesion or abnormal pigmentation'},
+            {'id': 'DERM_NEVUS', 'label_en': 'Benign melanocytic nevus with symmetry and uniform pigmentation'},
+            {'id': 'DERM_SEBORRHEIC', 'label_en': 'Seborrheic keratosis (benign warty lesion)'},
+            {'id': 'DERM_MELANOMA', 'label_en': 'Malignant melanoma with asymmetry, irregular borders, and color variegation'},
+            {'id': 'DERM_BCC', 'label_en': 'Basal cell carcinoma (pearly or ulcerated lesion)'},
+            {'id': 'DERM_SCC', 'label_en': 'Squamous cell carcinoma (crusty or budding lesion)'},
+            {'id': 'DERM_INFLAMMATORY', 'label_en': 'Inflammatory skin lesion (Eczema, Psoriasis)'}
+        ],
+        'logic_gate': {
+            'prompt': 'Is there a visible skin lesion?',
+            'labels': ['No visible skin lesion', 'Visible skin lesion (pigmented or non-pigmented)'],
+            'penalty_target': 'ALL_PATHOLOGY', 
+            'abnormal_index': 0 
+        }
+    },
+    'Histology': {
+        'id': 'DOM_HISTOLOGY',
+        'domain_prompt': 'Microscopic analysis of a histological section (H&E stain)',
+        'specific_labels': [
+            {'id': 'HIST_HEALTHY_BREAST', 'label_en': 'Healthy breast tissue with preserved lobular architecture'},
+            {'id': 'HIST_HEALTHY_PROSTATE', 'label_en': 'Healthy prostatic tissue with regular glands'},
+            {'id': 'HIST_IDC_BREAST', 'label_en': 'Invasive ductal carcinoma (Disorganized cells)'},
+            {'id': 'HIST_ADENO_PROSTATE', 'label_en': 'Prostate adenocarcinoma (Gland fusion)'},
+            {'id': 'HIST_DYSPLASIA', 'label_en': 'Cervical dysplasia or intraepithelial neoplasia'},
+            {'id': 'HIST_COLON_CA', 'label_en': 'Colon cancer tumor tissue'},
+            {'id': 'HIST_LUNG_CA', 'label_en': 'Lung cancer tumor tissue'},
+            {'id': 'HIST_ADIPOSE', 'label_en': 'Adipose tissue (Fat) or connective stroma'},
+            {'id': 'HIST_ARTIFACT', 'label_en': 'Preparation artifact, empty area, or blurred region'} 
+        ],
+        'logic_gate': {
+            'prompt': 'Assess histological validity of the image',
+            'labels': ['Adequate H&E tissue section', 'Artifact, empty area, or blurred region'],
+            'penalty_target': 'ALL_DIAGNOSIS',
+            'abnormal_index': 1
+        }
+    },
+    'Ophthalmology': {
+        'id': 'DOM_OPHTHALMOLOGY',
+        'domain_prompt': 'Fundus photography (Retina)',
+        'specific_labels': [
+            {'id': 'OPH_NORMAL', 'label_en': 'Normal retina with visible optic disc and macula'},
+            {'id': 'OPH_DIABETIC', 'label_en': 'Diabetic retinopathy (hemorrhages, exudates)'},
+            {'id': 'OPH_GLAUCOMA', 'label_en': 'Glaucoma (optic disc cupping)'},
+            {'id': 'OPH_AMD', 'label_en': 'Macular degeneration (drusen or atrophy)'}
+        ],
+        'logic_gate': {
+             'prompt': 'Is the fundus image clinically interpretable?',
+             'labels': ['Good quality fundus image', 'Poor quality, uninterpretable or partial view'],
+             'penalty_target': 'ALL_DIAGNOSIS',
+             'abnormal_index': 1
+        }
+    },
+    'Orthopedics': {
+        'id': 'DOM_ORTHOPEDICS',
+        'domain_prompt': 'Bone X-Ray (Musculoskeletal)',
+        'stage_1_triage': {
+            'prompt': 'Anatomical region identification',
+            'labels': [
+                'Other x-ray view (Chest, Hand, Foot, Pediatric) - OUT OF DISTRIBUTION',
+                'A knee x-ray view (Knee Joint)'
+            ]
+        },
+        'specific_labels': [ 
+             {'id': 'ORTH_OA_SEVERE', 'label_en': 'Severe osteoarthritis (Grade 4)'}, 
+             {'id': 'ORTH_OA_MODERATE', 'label_en': 'Moderate osteoarthritis (Grade 2-3)'}, 
+             {'id': 'ORTH_NORMAL', 'label_en': 'Normal knee'}, 
+             {'id': 'ORTH_IMPLANT', 'label_en': 'Implant'}
+        ],
+        'stage_2_diagnosis': {
+            'prompt': 'Knee Osteoarthritis Severity Assessment',
+            'labels': [
+                {'id': 'ORTH_OA_SEVERE', 'label_en': 'Severe osteoarthritis with bone-on-bone contact (Grade 4)'},
+                {'id': 'ORTH_OA_MODERATE', 'label_en': 'Moderate osteoarthritis with definite joint space narrowing (Grade 2-3)'},
+                {'id': 'ORTH_NORMAL', 'label_en': 'Normal knee joint with preserved joint space (Grade 0-1)'},
+                {'id': 'ORTH_IMPLANT', 'label_en': 'Total knee arthroplasty (TKA) with metallic implant'}, 
+                {'id': 'ORTH_FRACTURE', 'label_en': 'Acute knee fracture or dislocation'}
+            ]
+        },
+        'logic_gate': {
+            'prompt': 'Is there a metallic implant?',
+            'labels': ['Native knee joint', 'Knee with metallic implant (Arthroplasty)'],
+            'penalty_target': 'ORTH_OA', # Logic target string match (Prefix)
+            'abnormal_index': 1
+        }
+    }
+}
+
+# =========================================================================
+# FRENCH TRANSLATIONS (USER INTERFACE ONLY)
+# =========================================================================
+# - Strict Mapping: ID -> {title, description}
+# - No dynamic translation allowed.
+
+LABEL_TRANSLATIONS_FR = {
+    # --- THORACIC ---
+    'TH_NORMAL': {
+        'short': 'Thorax sans anomalie',
+        'long': 'Silhouette cardiaque normale, poumons clairs, pas d’épanchement.',
+        'severity': 'low'
+    },
+    'TH_PNEUMONIA_VIRAL': {
+        'short': 'Pneumonie Virale / Atypique',
+        'long': 'Opacités interstitielles diffuses ou verre dépoli.',
+        'severity': 'high'
+    },
+    'TH_PNEUMONIA_BACT': {
+        'short': 'Pneumonie Bactérienne',
+        'long': 'Consolidation alvéolaire focale avec bronchogramme aérien.',
+        'severity': 'high'
+    },
+    'TH_PNEUMOTHORAX': {
+        'short': 'Pneumothorax',
+        'long': 'Présence possible d’air dans la cavité pleurale (collapsus).',
+        'severity': 'emergency'
+    },
+    'TH_PLEURAL_EFFUSION': {
+        'short': 'Épanchement Pleural',
+        'long': 'Accumulation de liquide dans l’espace pleural.',
+        'severity': 'medium'
+    },
+    'TH_CARDIOMEGALY': {
+        'short': 'Cardiomégalie (Poumons clairs)',
+        'long': 'Silhouette cardiaque augmentée de taille sans signe d’œdème pulmonaire.',
+        'severity': 'medium'
+    },
+    'TH_CARDIOMEGALY_EDEMA': {
+        'short': 'Cardiomégalie avec Stase',
+        'long': 'Cœur augmenté de taille associé à une congestion pulmonaire.',
+        'severity': 'high'
+    },
+    'TH_EDEMA': {
+        'short': 'Œdème Pulmonaire',
+        'long': 'Surcharge liquidienne pulmonaire (sans cardiomégalie évidente).',
+        'severity': 'high'
+    },
+    'TH_NODULE': {
+        'short': 'Nodule ou Masse Pulmonaire',
+        'long': 'Lésion focale suspecte nécessitant un scanner de contrôle.',
+        'severity': 'high'
+    },
+    'TH_ATELECTASIS': {
+        'short': 'Atélectasie',
+        'long': 'Affaissement d’une partie du poumon.',
+        'severity': 'medium'
+    },
+
+    # --- DERMATOLOGY ---
+    'DERM_NORMAL': {
+        'short': 'Peau saine / Pas de lésion',
+        'long': 'Aucune lésion dermatologique suspecte visible.',
+        'severity': 'low'
+    },
+    'DERM_NEVUS': {
+        'short': 'Nævus Bénin (Grain de beauté)',
+        'long': 'Lésion régulière, symétrique et homogène.',
+        'severity': 'low'
+    },
+    'DERM_SEBORRHEIC': {
+        'short': 'Kératose Séborrhéique',
+        'long': 'Lésion bénigne fréquente ("verrue de vieillesse").',
+        'severity': 'low'
+    },
+    'DERM_MELANOMA': {
+        'short': 'Suspicion de Mélanome',
+        'long': 'Lésion pigmentée asymétrique, bords irréguliers (critères ABCDE). Urgence.',
+        'severity': 'emergency'
+    },
+    'DERM_BCC': {
+        'short': 'Carcinome Basocellulaire',
+        'long': 'Lésion perlée ou ulcérée suggérant un carcinome non-mélanique.',
+        'severity': 'high'
+    },
+    'DERM_SCC': {
+        'short': 'Carcinome Épidermoïde',
+        'long': 'Lésion croûteuse ou bourgeonnante suspecte.',
+        'severity': 'high'
+    },
+    'DERM_INFLAMMATORY': {
+        'short': 'Lésion Inflammatoire',
+        'long': 'Aspect compatible avec eczéma, psoriasis ou dermatite.',
+        'severity': 'medium'
+    },
+
+    # --- HISTOLOGY ---
+    'HIST_ARTIFACT': {
+        'short': 'Qualité Insuffisante (Artefact)',
+        'long': 'Tissu non interprétable (section vide, floue ou artefact technique).',
+        'severity': 'none'
+    },
+    'HIST_HEALTHY_BREAST': {
+        'short': 'Tissu Mammaire Sain',
+        'long': 'Architecture lobulaire préservée.',
+        'severity': 'low'
+    },
+    'HIST_IDC_BREAST': {
+        'short': 'Carcinome Canalaire Infiltrant',
+        'long': 'Prolifération cellulaire désorganisée invasive (Sein).',
+        'severity': 'high'
+    },
+    'HIST_HEALTHY_PROSTATE': {
+        'short': 'Tissu Prostatique Sain',
+        'long': 'Glandes régulières, stroma normal.',
+        'severity': 'low'
+    },
+    'HIST_ADENO_PROSTATE': {
+        'short': 'Adénocarcinome Prostatique',
+        'long': 'Fusion glandulaire et atypies cytonucléaires.',
+        'severity': 'high'
+    },
+    'HIST_COLON_CA': {'short': 'Cancer Colorectal', 'long': 'Tissu tumoral colique.', 'severity': 'high'},
+    'HIST_LUNG_CA': {'short': 'Cancer Pulmonaire', 'long': 'Tissu tumoral pulmonaire.', 'severity': 'high'},
+    'HIST_DYSPLASIA': {'short': 'Dysplasie / CIN', 'long': 'Anomalies précancéreuses.', 'severity': 'medium'},
+    'HIST_ADIPOSE': {'short': 'Tissu Adipeux / Stroma', 'long': 'Tissu de soutien normal.', 'severity': 'low'},
+
+    # --- OPHTHALMOLOGY ---
+    'OPH_NORMAL': {
+        'short': 'Fond d’œil Normal',
+        'long': 'Rétine, macula et papille d’aspect sain.',
+        'severity': 'low'
+    },
+    'OPH_DIABETIC': {
+        'short': 'Rétinopathie Diabétique',
+        'long': 'Présence d’hémorragies, exsudats ou anévrismes.',
+        'severity': 'high'
+    },
+    'OPH_GLAUCOMA': {
+        'short': 'Suspicion de Glaucome',
+        'long': 'Excavation papillaire (cup/disc ratio) augmentée.',
+        'severity': 'high'
+    },
+    'OPH_AMD': {
+        'short': 'DMLA',
+        'long': 'Dégénérescence Maculaire (drusens ou atrophie).',
+        'severity': 'medium'
+    },
+
+    # --- ORTHOPEDICS ---
+    'ORTH_NORMAL': {
+        'short': 'Genou Normal',
+        'long': 'Interligne articulaire préservé, pas d’ostéophyte.',
+        'severity': 'low'
+    },
+    'ORTH_OA_MODERATE': {
+        'short': 'Arthrose Modérée (Grade 2-3)',
+        'long': 'Pincement articulaire visible et ostéophytes.',
+        'severity': 'medium'
+    },
+    'ORTH_OA_SEVERE': {
+        'short': 'Arthrose Sévère (Grade 4)',
+        'long': 'Disparition de l’interligne (os sur os), déformation.',
+        'severity': 'high'
+    },
+    'ORTH_IMPLANT': {
+        'short': 'Prothèse Totale (PTG)',
+        'long': 'Genou avec implant métallique (Arthroplastie).',
+        'severity': 'low'
+    },
+    'ORTH_FRACTURE': {
+        'short': 'Fracture Récente / Luxation',
+        'long': 'Solution de continuité osseuse ou perte de congruence.',
+        'severity': 'emergency'
+    }
+}
+
+DOMAIN_TRANSLATIONS_FR = {
+    'Thoracic': 'Radiographie Thoracique',
+    'Dermatology': 'Dermatoscopie',
+    'Histology': 'Histopathologie (H&E)',
+    'Ophthalmology': 'Fond d’Oeil (Rétine)',
+    'Orthopedics': 'Radiographie Osseuse'
+}