Merge branch 'master' of github.com:josegcpa/adell-mri

adell_mri/entrypoints/classification/test.py

@@ -37,6 +37,7 @@ def main(arguments):
             "image_masking",
             "image_crop_from_mask",
             "filter_on_keys",
+            "fill_missing_with_placeholder",
             "possible_labels",
             "positive_labels",
             "label_groups",
@@ -82,6 +83,7 @@ def main(arguments):
         clinical_feature_keys = args.clinical_feature_keys
 
     data_dict = Dataset(args.dataset_json, rng=rng, verbose=True)
+    data_dict.fill_missing_with_value(args.fill_missing_with_placeholder)
     presence_keys = args.image_keys + [args.label_keys] + clinical_feature_keys
     if args.mask_key is not None:
         presence_keys.append(args.mask_key)

adell_mri/entrypoints/classification/train.py

@@ -63,6 +63,7 @@ def main(arguments):
             "subsample_size",
             "subsample_training_data",
             "filter_on_keys",
+            "fill_missing_with_placeholder",
             "val_from_train",
             "config_file",
             "dev",
@@ -128,6 +129,7 @@ def main(arguments):
     n_devices = 1 if isinstance(devices, str) else n_devices
 
     data_dict = Dataset(args.dataset_json, rng=rng)
+    data_dict.fill_missing_with_value(args.fill_missing_with_placeholder)
 
     if args.clinical_feature_keys is None:
         clinical_feature_keys = []

adell_mri/entrypoints/classification_deconfounder/test.py

@@ -41,6 +41,7 @@ def main(arguments):
             "image_masking",
             "image_crop_from_mask",
             "filter_on_keys",
+            "fill_missing_with_placeholder",
             "possible_labels",
             "positive_labels",
             "label_groups",
@@ -86,6 +87,7 @@ def main(arguments):
         clinical_feature_keys = args.clinical_feature_keys
 
     data_dict = Dataset(args.dataset_json, rng=rng, verbose=True)
+    data_dict.fill_missing_with_value(args.fill_missing_with_placeholder)
     presence_keys = args.image_keys + [args.label_keys] + clinical_feature_keys
     if args.mask_key is not None:
         presence_keys.append(args.mask_key)

adell_mri/entrypoints/classification_deconfounder/train.py

@@ -50,6 +50,7 @@ def main(arguments):
             "cat_confounder_keys",
             "cont_confounder_keys",
             "exclude_surrogate_variables",
+            "fill_missing_with_placeholder",
             "n_features_deconfounder",
             "mask_key",
             "image_masking",
@@ -131,6 +132,7 @@ def main(arguments):
     n_devices = 1 if isinstance(devices, str) else n_devices
 
     data_dict = Dataset(args.dataset_json, rng=rng)
+    data_dict.fill_missing_with_value(args.fill_missing_with_placeholder)
 
     if args.excluded_ids_from_training_data is not None:
         excluded_ids_from_training_data = parse_ids(

adell_mri/entrypoints/classification_ensemble/test.py

@@ -42,6 +42,7 @@ def main(arguments):
             "positive_labels",
             "label_groups",
             "filter_on_keys",
+            "fill_missing_with_placeholder",
             "excluded_ids",
             "cache_rate",
             "target_spacing",
@@ -74,6 +75,7 @@ def main(arguments):
     output_file = open(args.metric_path, "w")
 
     data_dict = json.load(open(args.dataset_json, "r"))
+    data_dict.fill_missing_with_value(args.fill_missing_with_placeholder)
 
     if args.clinical_feature_keys is None:
         clinical_feature_keys = []

adell_mri/entrypoints/classification_ensemble/train.py

@@ -52,6 +52,7 @@ def main(arguments):
             "t2_keys",
             "adc_keys",
             "filter_on_keys",
+            "fill_missing_with_placeholder",
             "possible_labels",
             "positive_labels",
             "label_groups",
@@ -130,6 +131,7 @@ def main(arguments):
     output_file = open(args.metric_path, "w")
 
     data_dict = Dataset(args.dataset_json, rng=rng)
+    data_dict.fill_missing_with_value(args.fill_missing_with_placeholder)
 
     if args.clinical_feature_keys is None:
         clinical_feature_keys = []

adell_mri/entrypoints/classification_mil/test.py

@@ -37,6 +37,7 @@ def main(arguments):
             "adc_keys",
             "label_keys",
             "filter_on_keys",
+            "fill_missing_with_placeholder",
             "possible_labels",
             "positive_labels",
             "label_groups",
@@ -79,6 +80,7 @@ def main(arguments):
     accelerator, devices, strategy = get_devices(args.dev)
 
     data_dict = Dataset(args.dataset_json, rng=rng, verbose=True)
+    data_dict.fill_missing_with_value(args.fill_missing_with_placeholder)
     if args.excluded_ids is not None:
         data_dict.subsample_dataset(excluded_key_list=args.excluded_ids)
 

adell_mri/entrypoints/classification_mil/train.py

@@ -48,6 +48,7 @@ def main(arguments):
             "t2_keys",
             "label_keys",
             "filter_on_keys",
+            "fill_missing_with_placeholder",
             "possible_labels",
             "positive_labels",
             "label_groups",
@@ -126,6 +127,7 @@ def main(arguments):
     output_file = open(args.metric_path, "w")
 
     data_dict = Dataset(args.dataset_json, rng=rng)
+    data_dict.fill_missing_with_value(args.fill_missing_with_placeholder)
 
     if args.excluded_ids_from_training_data is not None:
         excluded_ids_from_training_data = parse_ids(
@@ -208,7 +210,7 @@ def main(arguments):
     transforms_common = get_transforms("pre", **transform_arguments)
     transforms_train = monai.transforms.Compose(
         [
-            get_augmentations(**augment_arguments),
+            get_augmentations(**augment_arguments, mask_key=None),
             *get_transforms("post", **transform_arguments),
             EinopsRearranged("image", "c h w d -> 1 h w (d c)"),
             ScaleIntensityAlongDimd("image", dim=-1),