Merge pull request #64 from BrainLesion/enable_none_outputs

Enable_none_outputs

Author: neuronflow

brainles_preprocessing/modality.py

@@ -42,15 +42,23 @@ def __init__(
         self,
         modality_name: str,
         input_path: str,
-        raw_bet_output_path: str = None,
-        raw_skull_output_path: str = None,
-        normalized_bet_output_path: str = None,
-        normalized_skull_output_path: str = None,
+        raw_bet_output_path: Optional[str] = None,
+        raw_skull_output_path: Optional[str] = None,
+        normalized_bet_output_path: Optional[str] = None,
+        normalized_skull_output_path: Optional[str] = None,
         normalizer: Optional[Normalizer] = None,
         atlas_correction: bool = True,
     ) -> None:
+        # basics
         self.modality_name = modality_name
+
         self.input_path = turbopath(input_path)
+        self.current = self.input_path
+
+        self.normalizer = normalizer
+        self.atlas_correction = atlas_correction
+
+        # check that atleast one output is generated
         if (
             raw_bet_output_path is None
             and normalized_bet_output_path is None
@@ -60,30 +68,42 @@ def __init__(
             raise ValueError(
                 "All output paths are None. At least one output path must be provided."
             )
-        self.raw_bet_output_path = turbopath(raw_bet_output_path)
-        self.raw_skull_output_path = turbopath(raw_skull_output_path)
+
+        # handle input paths
+        if raw_bet_output_path is not None:
+            self.raw_bet_output_path = turbopath(raw_bet_output_path)
+        else:
+            self.raw_bet_output_path = raw_bet_output_path
+
+        if raw_skull_output_path is not None:
+            self.raw_skull_output_path = turbopath(raw_skull_output_path)
+        else:
+            self.raw_skull_output_path = raw_skull_output_path
+
         if normalized_bet_output_path is not None:
             if normalizer is None:
                 raise ValueError(
                     "A normalizer must be provided if normalized_bet_output_path is not None."
                 )
-        self.normalized_bet_output_path = turbopath(normalized_bet_output_path)
+            self.normalized_bet_output_path = turbopath(normalized_bet_output_path)
+        else:
+            self.normalized_bet_output_path = normalized_bet_output_path
 
         if normalized_skull_output_path is not None:
             if normalizer is None:
                 raise ValueError(
                     "A normalizer must be provided if normalized_skull_output_path is not None."
                 )
-        self.normalized_skull_output_path = turbopath(normalized_skull_output_path)
-
-        self.normalizer = normalizer
-        self.atlas_correction = atlas_correction
-
-        self.current = self.input_path
+            self.normalized_skull_output_path = turbopath(normalized_skull_output_path)
+        else:
+            self.normalized_skull_output_path = normalized_skull_output_path
 
     @property
     def bet(self) -> bool:
-        return any([self.raw_bet_output_path, self.normalized_bet_output_path])
+        return any(
+            path is not None
+            for path in [self.raw_bet_output_path, self.normalized_skull_output_path]
+        )
 
     def normalize(
         self,

brainles_preprocessing/preprocessor.py

@@ -203,12 +203,12 @@ def run(
 
         # now we save images that are not skullstripped
         for modality in self.all_modalities:
-            if modality.raw_skull_output_path:
+            if modality.raw_skull_output_path is not None:
                 modality.save_current_image(
                     modality.raw_skull_output_path,
                     normalization=False,
                 )
-            if modality.normalized_skull_output_path:
+            if modality.normalized_skull_output_path is not None:
                 modality.save_current_image(
                     modality.normalized_skull_output_path,
                     normalization=True,
@@ -240,12 +240,12 @@ def run(
 
         # now we save images that are skullstripped
         for modality in self.all_modalities:
-            if modality.raw_bet_output_path:
+            if modality.raw_bet_output_path is not None:
                 modality.save_current_image(
                     modality.raw_bet_output_path,
                     normalization=False,
                 )
-            if modality.normalized_bet_output_path:
+            if modality.normalized_bet_output_path is not None:
                 modality.save_current_image(
                     modality.normalized_bet_output_path,
                     normalization=True,
@@ -256,7 +256,7 @@ def _save_output(
         src: str,
         save_dir: Optional[str],
     ):
-        if save_dir:
+        if save_dir is not None:
             save_dir = turbopath(save_dir)
             shutil.copytree(
                 src=src,

example/example_modality_centric_preprocessor.py

@@ -1,6 +1,4 @@
 # This script is an example of how to use the ModalityCentricPreprocessor class to preprocess a set of MR images. It is only here for quick development and testing purposes. It is not intended to be used in a production environment.
-import datetime
-
 from auxiliary.normalization.percentile_normalizer import PercentileNormalizer
 from auxiliary.turbopath import turbopath
 from tqdm import tqdm
@@ -13,128 +11,107 @@
 
 def preprocess(inputDir):
     inputDir = turbopath(inputDir)
-    try:
-        print("*** start ***")
-
-        # where are the raw mr files?
-        btk_raw_dir = turbopath(inputDir)
-
-        # is the exam already processed?
-        brainles_dir = turbopath(inputDir) + "/" + inputDir.name + "_brainles"
-        raw_bet_dir = brainles_dir / "raw_bet"
-        norm_bet_dir = brainles_dir / "normalized_bet"
-        raw_skull_dir = brainles_dir / "raw_skull"
-        norm_skull_dir = brainles_dir / "normalized_skull"
-
-        # if not os.path.exists(prep_dir):
-        # if os.path.exists(prep_dir):
-        t1_file = btk_raw_dir.files("*t1.nii.gz")
-        t1c_file = btk_raw_dir.files("*t1c.nii.gz")
-        t2_file = btk_raw_dir.files("*t2.nii.gz")
-        flair_file = btk_raw_dir.files("*fla.nii.gz")
-
-        if len(t1_file) == len(t1c_file) == len(t2_file) == len(flair_file) == 1:
-            # print(t1_file)
-            # print(t1c_file)
-            # print(t2_file)
-            # print(flair_file)
-
-            t1File = t1_file[0]
-            t1cFile = t1c_file[0]
-            t2File = t2_file[0]
-            flaFile = flair_file[0]
-
-            # normalizer
-            percentile_normalizer = PercentileNormalizer(
-                lower_percentile=0.1,
-                upper_percentile=99.9,
-                lower_limit=0,
-                upper_limit=1,
-            )
-
-            # define modalities
-            center = Modality(
-                modality_name="t1c",
-                input_path=t1cFile,
-                raw_bet_output_path=raw_bet_dir / inputDir.name + "_t1c_bet_raw.nii.gz",
+    print("*** start ***")
+
+    # where are the raw mr files?
+    brainles_dir = turbopath(inputDir) + "/" + inputDir.name + "_brainles"
+
+    raw_bet_dir = brainles_dir / "raw_bet"
+    norm_bet_dir = brainles_dir / "normalized_bet"
+    raw_skull_dir = brainles_dir / "raw_skull"
+    norm_skull_dir = brainles_dir / "normalized_skull"
+
+    t1_file = inputDir.files("*t1.nii.gz")
+    t1c_file = inputDir.files("*t1c.nii.gz")
+    t2_file = inputDir.files("*t2.nii.gz")
+    flair_file = inputDir.files("*fla.nii.gz")
+    if len(t1_file) == len(t1c_file) == len(t2_file) == len(flair_file) == 1:
+        # print(t1_file)
+        # print(t1c_file)
+        # print(t2_file)
+        # print(flair_file)
+        t1File = t1_file[0]
+        t1cFile = t1c_file[0]
+        t2File = t2_file[0]
+        flaFile = flair_file[0]
+        # normalizer
+        percentile_normalizer = PercentileNormalizer(
+            lower_percentile=0.1,
+            upper_percentile=99.9,
+            lower_limit=0,
+            upper_limit=1,
+        )
+        # define modalities
+        center = Modality(
+            modality_name="t1c",
+            input_path=t1cFile,
+            raw_bet_output_path=raw_bet_dir / inputDir.name + "_t1c_bet_raw.nii.gz",
+            raw_skull_output_path=raw_skull_dir / inputDir.name
+            + "_t1c_skull_raw.nii.gz",
+            normalized_bet_output_path=norm_bet_dir / inputDir.name
+            + "_t1c_bet_normalized.nii.gz",
+            normalized_skull_output_path=norm_skull_dir / inputDir.name
+            + "_t1c_skull_normalized.nii.gz",
+            atlas_correction=True,
+            normalizer=percentile_normalizer,
+        )
+        moving_modalities = [
+            Modality(
+                modality_name="t1",
+                input_path=t1File,
+                raw_bet_output_path=raw_bet_dir / inputDir.name + "_t1_bet_raw.nii.gz",
                 raw_skull_output_path=raw_skull_dir / inputDir.name
-                + "_t1c_skull_raw.nii.gz",
+                + "_t1_skull_raw.nii.gz",
                 normalized_bet_output_path=norm_bet_dir / inputDir.name
-                + "_t1c_bet_normalized.nii.gz",
+                + "_t1_bet_normalized.nii.gz",
                 normalized_skull_output_path=norm_skull_dir / inputDir.name
-                + "_t1c_skull_normalized.nii.gz",
+                + "_t1_skull_normalized.nii.gz",
                 atlas_correction=True,
                 normalizer=percentile_normalizer,
-            )
-
-            moving_modalities = [
-                Modality(
-                    modality_name="t1",
-                    input_path=t1File,
-                    raw_bet_output_path=raw_bet_dir / inputDir.name
-                    + "_t1_bet_raw.nii.gz",
-                    raw_skull_output_path=raw_skull_dir / inputDir.name
-                    + "_t1_skull_raw.nii.gz",
-                    normalized_bet_output_path=norm_bet_dir / inputDir.name
-                    + "_t1_bet_normalized.nii.gz",
-                    normalized_skull_output_path=norm_skull_dir / inputDir.name
-                    + "_t1_skull_normalized.nii.gz",
-                    atlas_correction=True,
-                    normalizer=percentile_normalizer,
-                ),
-                Modality(
-                    modality_name="t2",
-                    input_path=t2File,
-                    raw_bet_output_path=raw_bet_dir / inputDir.name
-                    + "_t2_bet_raw.nii.gz",
-                    raw_skull_output_path=raw_skull_dir / inputDir.name
-                    + "_t2_skull_raw.nii.gz",
-                    normalized_bet_output_path=norm_bet_dir / inputDir.name
-                    + "_t2_bet_normalized.nii.gz",
-                    normalized_skull_output_path=norm_skull_dir / inputDir.name
-                    + "_t2_skull_normalized.nii.gz",
-                    atlas_correction=True,
-                    normalizer=percentile_normalizer,
-                ),
-                Modality(
-                    modality_name="flair",
-                    input_path=flaFile,
-                    raw_bet_output_path=raw_bet_dir / inputDir.name
-                    + "_fla_bet_raw.nii.gz",
-                    raw_skull_output_path=raw_skull_dir / inputDir.name
-                    + "_fla_skull_raw.nii.gz",
-                    normalized_bet_output_path=norm_bet_dir / inputDir.name
-                    + "_fla_bet_normalized.nii.gz",
-                    normalized_skull_output_path=norm_skull_dir / inputDir.name
-                    + "_fla_skull_normalized.nii.gz",
-                    atlas_correction=True,
-                    normalizer=percentile_normalizer,
-                ),
-            ]
-
-            preprocessor = Preprocessor(
-                center_modality=center,
-                moving_modalities=moving_modalities,
-                registrator=NiftyRegRegistrator(),
-                brain_extractor=HDBetExtractor(),
-                temp_folder="tempo",
-                limit_cuda_visible_devices="1",
-            )
-
-            preprocessor.run(
-                save_dir_coregistration=brainles_dir + "/co-registration",
-                save_dir_atlas_registration=brainles_dir + "/atlas-registration",
-                save_dir_atlas_correction=brainles_dir + "/atlas-correction",
-                save_dir_brain_extraction=brainles_dir + "/brain-extraction",
-            )
-
-    except Exception as e:
-        print("error: " + str(e))
-        print("conversion error for:", inputDir)
-
-        time = str(datetime.datetime.now().time())
-
-        print("** finished:", inputDir.name, "at:", time)
+            ),
+            Modality(
+                modality_name="t2",
+                input_path=t2File,
+                raw_bet_output_path=raw_bet_dir / inputDir.name + "_t2_bet_raw.nii.gz",
+                raw_skull_output_path=raw_skull_dir / inputDir.name
+                + "_t2_skull_raw.nii.gz",
+                normalized_bet_output_path=norm_bet_dir / inputDir.name
+                + "_t2_bet_normalized.nii.gz",
+                normalized_skull_output_path=norm_skull_dir / inputDir.name
+                + "_t2_skull_normalized.nii.gz",
+                atlas_correction=True,
+                normalizer=percentile_normalizer,
+            ),
+            Modality(
+                modality_name="flair",
+                input_path=flaFile,
+                raw_bet_output_path=raw_bet_dir / inputDir.name + "_fla_bet_raw.nii.gz",
+                raw_skull_output_path=raw_skull_dir / inputDir.name
+                + "_fla_skull_raw.nii.gz",
+                normalized_bet_output_path=norm_bet_dir / inputDir.name
+                + "_fla_bet_normalized.nii.gz",
+                normalized_skull_output_path=norm_skull_dir / inputDir.name
+                + "_fla_skull_normalized.nii.gz",
+                atlas_correction=True,
+                normalizer=percentile_normalizer,
+            ),
+        ]
+
+        preprocessor = Preprocessor(
+            center_modality=center,
+            moving_modalities=moving_modalities,
+            registrator=NiftyRegRegistrator(),
+            brain_extractor=HDBetExtractor(),
+            temp_folder="temporary_directory",
+            limit_cuda_visible_devices="0",
+        )
+
+        preprocessor.run(
+            save_dir_coregistration=brainles_dir + "/co-registration",
+            save_dir_atlas_registration=brainles_dir + "/atlas-registration",
+            save_dir_atlas_correction=brainles_dir + "/atlas-correction",
+            save_dir_brain_extraction=brainles_dir + "/brain-extraction",
+        )
 
 
 ### *** GOGOGO *** ###