padded radiological gradings

SPIDER.py

@@ -418,7 +418,14 @@ class SPIDER(datasets.GeneratorBasedBuilder):
             ]
             if patient_grades:
                 grades_dict[str(patient_id)] = patient_grades
-    
+                
+        # Determine maximum number of radiological gradings per patient
+        max_ivd = 0
+        for temp_dict_1 in grades_dict.values():
+            for temp_dict_2 in temp_dict_1:
+                if int(temp_dict_2['IVD label']) > max_ivd:
+                    max_ivd = int(temp_dict_2['IVD label'])
+
         # Import image and mask data
         image_files = [
             file for file in os.listdir(os.path.join(paths_dict['images'], 'images'))
@@ -496,7 +503,21 @@ class SPIDER(datasets.GeneratorBasedBuilder):
                     if k not in ['Patient', 'IVD label']
                 }
                 patient_grades_dict[key] = value
-        
+                
+            # Pad patient radiological gradings so that data for all patients
+            # have the same dimensions
+            for i in range(len(patient_grades_dict) + 1, max_ivd + 1):
+                patient_grades_dict[f'IVD{i}'] = {
+                    "Modic": "",
+                    "UP endplate": "",
+                    "LOW endplate": "",
+                    "Spondylolisthesis": "",
+                    "Disc herniation": "",
+                    "Disc narrowing": "",
+                    "Disc bulging": "",
+                    "Pfirrman grade": "",
+                }
+
             # Prepare example return dict
             return_dict = {'patient_id':patient_id, 'scan_type':scan_type}
             # if raw_image: