Merge pull request #29 from BrainLesion/feat/refactor_brain_extraction

Refactor brain extraction

brainles_preprocessing/brain_extraction/brain_extractor.py

@@ -1,54 +1,79 @@
 # TODO add typing and docs
 from abc import abstractmethod
+import os
 
 import nibabel as nib
 import numpy as np
 from brainles_hd_bet import run_hd_bet
 
+from auxiliary.nifti.io import read_nifti, write_nifti
+from auxiliary.turbopath import name_extractor
+
+
+from shutil import copyfile
+
 
 class BrainExtractor:
     @abstractmethod
     def extract(
         self,
-        input_image,
-        output_image,
-        log_file,
-        mode,
-    ):
+        input_image_path: str,
+        masked_image_path: str,
+        brain_mask_path: str,
+        log_file_path: str,
+        # TODO convert mode to enum
+        mode: str,
+    ) -> None:
         pass
 
     def apply_mask(
         self,
-        input_image,
-        mask_image,
-        output_image,
-    ):
-        """masks images with brain masks"""
-        inputnifti = nib.load(input_image)
-        mask = nib.load(mask_image)
+        input_image_path: str,
+        mask_image_path: str,
+        masked_image_path: str,
+    ) -> None:
+        """
+        Apply a brain mask to an input image.
 
-        # mask it
-        masked_file = np.multiply(inputnifti.get_fdata(), mask.get_fdata())
-        masked_file = nib.Nifti1Image(masked_file, inputnifti.affine, inputnifti.header)
+        Parameters:
+        - input_image_path (str): Path to the input image (NIfTI format).
+        - mask_image_path (str): Path to the brain mask image (NIfTI format).
+        - masked_image_path (str): Path to save the resulting masked image (NIfTI format).
 
-        # save it
-        nib.save(masked_file, output_image)
+        Returns:
+        - str: Path to the saved masked image.
+        """
+
+        # read data
+        input_data = read_nifti(input_image_path)
+        mask_data = read_nifti(mask_image_path)
+
+        # mask and save it
+        masked_data = input_data * mask_data
+
+        write_nifti(
+            input_array=masked_data,
+            output_nifti_path=masked_image_path,
+            reference_nifti_path=input_image_path,
+            create_parent_directory=True,
+        )
 
 
 class HDBetExtractor(BrainExtractor):
     def extract(
         self,
-        input_image,
-        masked_image,
-        # TODO implement logging!
-        log_file,
-        mode="accurate",
-    ):
+        input_image_path: str,
+        masked_image_path: str,
+        brain_mask_path: str,
+        log_file_path: str = None,
+        # TODO convert mode to enum
+        mode: str = "accurate",
+    ) -> None:
         # GPU + accurate + TTA
         """skullstrips images with HD-BET generates a skullstripped file and mask"""
         run_hd_bet(
-            mri_fnames=[input_image],
-            output_fnames=[masked_image],
+            mri_fnames=[input_image_path],
+            output_fnames=[masked_image_path],
             # device=0,
             # TODO consider postprocessing
             # postprocess=False,
@@ -59,3 +84,15 @@ def extract(
             keep_mask=True,
             overwrite=True,
         )
+
+        hdbet_mask_path = (
+            masked_image_path.parent
+            + "/"
+            + name_extractor(masked_image_path)
+            + "_masked.nii.gz"
+        )
+
+        copyfile(
+            src=hdbet_mask_path,
+            dst=brain_mask_path,
+        )

brainles_preprocessing/modality.py

@@ -115,9 +115,9 @@ def apply_mask(
                 f"brain_masked__{self.modality_name}.nii.gz",
             )
             brain_extractor.apply_mask(
-                input_image=self.current,
-                mask_image=atlas_mask,
-                output_image=brain_masked,
+                input_image_path=self.current,
+                mask_image_path=atlas_mask,
+                masked_image_path=brain_masked,
             )
             self.current = brain_masked
 
@@ -153,9 +153,10 @@ def extract_brain_region(
         )
 
         brain_extractor.extract(
-            input_image=self.current,
-            masked_image=atlas_bet_cm,
-            log_file=bet_log,
+            input_image_path=self.current,
+            masked_image_path=atlas_bet_cm,
+            brain_mask_path=atlas_mask,
+            log_file_path=bet_log,
         )
         self.current = atlas_bet_cm
         return atlas_mask