[pre-commit.ci] auto fixes from pre-commit.com hooks

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Author: pre-commit-ci[bot]

monai/transforms/clinical_preprocessing.py

@@ -21,15 +21,15 @@ class UnsupportedModalityError(ValueError):
 def get_ct_preprocessing_pipeline() -> Compose:
     """
     Create a preprocessing pipeline for CT (Computed Tomography) images.
-    
+
     Returns:
         Compose: A transform composition for CT preprocessing.
-        
+
     The pipeline consists of:
     1. LoadImage - Load DICOM series
     2. EnsureChannelFirst - Add channel dimension
     3. ScaleIntensityRange - Scale Hounsfield Units (HU) from [-1000, 400] to [0, 1]
-    
+
     Note:
         The HU window [-1000, 400] is a common soft tissue window.
     """
@@ -43,15 +43,15 @@ def get_ct_preprocessing_pipeline() -> Compose:
 def get_mri_preprocessing_pipeline() -> Compose:
     """
     Create a preprocessing pipeline for MRI (Magnetic Resonance Imaging) images.
-    
+
     Returns:
         Compose: A transform composition for MRI preprocessing.
-        
+
     The pipeline consists of:
     1. LoadImage - Load DICOM series
     2. EnsureChannelFirst - Add channel dimension
     3. NormalizeIntensity - Normalize non-zero voxels
-    
+
     Note:
         Normalization is applied only to non-zero voxels to avoid bias from background.
     """
@@ -81,14 +81,14 @@ def preprocess_dicom_series(path: str, modality: str) -> MetaTensor:
     # Validate input type
     if not isinstance(modality, str):
         raise ModalityTypeError(f"modality must be a string, got {type(modality).__name__}")
-    
+
     # Normalize modality string (strip whitespace, convert to uppercase)
     modality_clean = modality.strip().upper()
-    
+
     # Map MRI to MR (treat as synonyms)
     if modality_clean == "MRI":
         modality_clean = "MR"
-    
+
     # Select appropriate preprocessing pipeline
     if modality_clean == "CT":
         pipeline = get_ct_preprocessing_pipeline()
@@ -99,15 +99,15 @@ def preprocess_dicom_series(path: str, modality: str) -> MetaTensor:
         raise UnsupportedModalityError(
             f"Unsupported modality '{modality}'. Supported modalities: {', '.join(supported)}"
         )
-    
+
     # Apply preprocessing pipeline
     return pipeline(path)
 
 
 # Export the public API
 __all__ = [
     "ModalityTypeError",
-    "UnsupportedModalityError", 
+    "UnsupportedModalityError",
     "get_ct_preprocessing_pipeline",
     "get_mri_preprocessing_pipeline",
     "preprocess_dicom_series",