relative paths and output folder paths for dataset.csv

examples/autotest.py

@@ -2,6 +2,7 @@
 import shutil
 import glob
 import pickle
+from imgtools.io.common import file_name_convention
 import numpy as np
 import sys
 
@@ -45,8 +46,8 @@ def __init__(self,
             warn_on_error=warn_on_error)
         self.overwrite = overwrite
         # pipeline configuration
-        self.input_directory = input_directory
-        self.output_directory = output_directory
+        self.input_directory = pathlib.Path(input_directory).as_posix()
+        self.output_directory = pathlib.Path(output_directory).as_posix()
         self.spacing = spacing
         self.existing = [None] #self.existing_patients()
 
@@ -110,8 +111,6 @@ def process_one_subject(self, subject_id):
 
             print(output_stream)
 
-            print(i, colname, "asdflkjqroigj")
-
             if read_results[i] is None:
                 print("The subject id: {} has no {}".format(subject_id, colname))
                 pass
@@ -222,9 +221,12 @@ def process_one_subject(self, subject_id):
                     metadata.update(pet.metadata)
 
                 print(subject_id, " SAVED PET")
+
+            metadata[f"output_folder_{colname}"] = pathlib.Path(subject_id, file_name_convention()[colname]).as_posix()
         #Saving all the metadata in multiple text files
         metadata["Modalities"] = str(list(subject_modalities))
         metadata["numRTSTRUCTs"] = num_rtstructs
+
         with open(pathlib.Path(self.output_directory,".temp",f'{subject_id}.pkl').as_posix(),'wb') as f:
             pickle.dump(metadata,f)
         return 
@@ -237,6 +239,12 @@ def save_data(self):
             with open(file,"rb") as f:
                 metadata = pickle.load(f)
             self.output_df.loc[subject_id, list(metadata.keys())] = list(metadata.values())
+        folder_renames = {}
+        for col in self.output_df.columns:
+            if col.startswith("folder"):
+                self.output_df[col] = self.output_df[col].apply(lambda x: pathlib.Path(x).as_posix().split(self.input_directory)[1][1:]) # rel path, exclude the slash at the beginning
+                folder_renames[col] = f"output_{col}"
+        self.output_df.rename(columns=folder_renames, inplace=True)
         self.output_df.to_csv(self.output_df_path)
         shutil.rmtree(pathlib.Path(self.output_directory, ".temp").as_posix())
 
@@ -265,16 +273,16 @@ def run(self):
     #                         visualize=False,
     #                         overwrite=True)
 
-    # pipeline = AutoPipeline(input_directory="C:/Users/qukev/BHKLAB/hnscc_testing/HNSCC",
-    #                         output_directory="C:/Users/qukev/BHKLAB/hnscc_testing_output",
-    #                         modalities="CT,RTSTRUCT",
-    #                         visualize=False,
-    #                         overwrite=True)
-    pipeline = AutoPipeline(input_directory="C:/Users/qukev/BHKLAB/hnscc_pet/PET",
-                            output_directory="C:/Users/qukev/BHKLAB/hnscc_pet_output",
-                            modalities="CT,PT",
+    pipeline = AutoPipeline(input_directory="C:/Users/qukev/BHKLAB/hnscc_testing/HNSCC",
+                            output_directory="C:/Users/qukev/BHKLAB/hnscc_testing_output",
+                            modalities="CT,RTSTRUCT",
                             visualize=False,
                             overwrite=True)
+    # pipeline = AutoPipeline(input_directory="C:/Users/qukev/BHKLAB/hnscc_pet/PET",
+    #                         output_directory="C:/Users/qukev/BHKLAB/hnscc_pet_output",
+    #                         modalities="CT,PT",
+    #                         visualize=False,
+    #                         overwrite=True)
 
     print(f'starting Pipeline...')
     pipeline.run()

imgtools/io/loaders.py

@@ -73,6 +73,8 @@ def read_dicom_series(path: str,
     if modality == 'CT':
         if hasattr(dicom_data, 'KVP'):
             metadata["KVP"] = str(dicom_data.KVP)
+        if hasattr(dicom_data, 'XRayTubeCurrent'):
+            metadata["XRayTubeCurrent"] = str(dicom_data.XRayTubeCurrent)
         if hasattr(dicom_data, 'ScanOptions'):
             metadata["ScanOptions"] = str(dicom_data.ScanOptions)
         if hasattr(dicom_data, 'ReconstructionAlgorithm'):
@@ -82,8 +84,8 @@ def read_dicom_series(path: str,
         if hasattr(dicom_data, 'ContrastFlowDuration'):
             metadata["ContrastFlowDuration"] = str(dicom_data.ContrastFlowDuration)
         # is this contrast type?
-        # if hasattr(dicom_data, 'ContrastBolusAgent'):
-        #     metadata["ContrastType"] = str(dicom_data.ContrastBolusAgent)
+        if hasattr(dicom_data, 'ContrastBolusAgent'):
+            metadata["ContrastType"] = str(dicom_data.ContrastBolusAgent)
     else: # MR
         if hasattr(dicom_data, 'AcquisitionTime'):
             metadata["AcquisitionTime"] = str(dicom_data.AcquisitionTime)
@@ -101,6 +103,10 @@ def read_dicom_series(path: str,
             metadata["MagneticFieldStrength"] = str(dicom_data.MagneticFieldStrength)
 
     # Number of Slices is avg. number slice?
+    if hasattr(dicom_data, 'BodyPartExamined'):
+        metadata["BodyPartExamined"] = str(dicom_data.BodyPartExamined)
+    if hasattr(dicom_data, 'DataCollectionDiameter'):
+        metadata["DataCollectionDiameter"] = str(dicom_data.DataCollectionDiameter)
     if hasattr(dicom_data, 'NumberofSlices'):
         metadata["NumberofSlices"] = str(dicom_data.NumberofSlices)
     # Slice Thickness is avg. slice thickness?
@@ -118,9 +124,6 @@ def read_dicom_series(path: str,
         metadata["ContrastType"] = str(dicom_data.ContrastBolusAgent)
     if hasattr(dicom_data, 'Manufacturer'):
         metadata["Manufacturer"] = str(dicom_data.Manufacturer)
-    # Which field of view?
-    # if hasattr(dicom_data, 'FieldOfViewDescription'):
-    #     metadata["FieldOfViewDescription"] = str(dicom_data.FieldOfViewDescription)
     # Scan Plane?
     if hasattr(dicom_data, 'ScanOptions'):
         metadata["ScanOptions"] = str(dicom_data.ScanOptions)
@@ -148,7 +151,7 @@ def read_dicom_pet(path,series=None):
 def read_dicom_auto(path, series=None):
     if path is None:
         return None
-    print(path, "asdlfkjqeroigjodfklsjg")
+    # print(path, "asdlfkjqeroigjodfklsjg")
     dcms = glob.glob(pathlib.Path(path, "*.dcm").as_posix())
     meta = dcmread(dcms[0])
     modality = meta.Modality

imgtools/modules/datagraph.py

@@ -403,6 +403,7 @@ def _get_df(self,
                 folder_save["patient_ID"] = df_connections["patient_ID_x"].iloc[0]
                 folder_save[f"series_{df_connections['modality_x'].iloc[0]}"] = comp[j]
                 folder_save[f"folder_{df_connections['modality_x'].iloc[0]}"] = df_connections["folder_x"].iloc[0]
+                print(f"folder_{df_connections['modality_x'].iloc[0]}", df_connections["folder_x"].iloc[0], "asdf")
                 temp_dfconn = df_connections[["series_y", "modality_y", "folder_y"]]
                 for k in range(len(temp_dfconn)):
                     #This loop stores connection of the CT

imgtools/modules/dose.py

@@ -50,6 +50,10 @@ def from_dicom_rtdose(cls, path):
         metadata = {}
         # metadata["DoseType"] = df.DoseType
         #return cls(img_dose, df, metadata)
+        if hasattr(df, 'BodyPartExamined'):
+            metadata["BodyPartExamined"] = str(df.BodyPartExamined)
+        if hasattr(df, 'DataCollectionDiameter'):
+            metadata["DataCollectionDiameter"] = str(df.DataCollectionDiameter)
         # Number of Slices is avg. number slice?
         if hasattr(df, 'NumberofSlices'):
             metadata["NumberofSlices"] = str(df.NumberofSlices)

imgtools/modules/pet.py

@@ -73,6 +73,10 @@ def from_dicom_pet(cls, path,series_id=None,type="SUV"):
         if hasattr(pet, 'RadionuclideHalfLife'):
             metadata["RadionuclideHalfLife"] = str(pet.RadionuclideHalfLife)
 
+        if hasattr(pet, 'BodyPartExamined'):
+            metadata["BodyPartExamined"] = str(pet.BodyPartExamined)
+        if hasattr(pet, 'DataCollectionDiameter'):
+            metadata["DataCollectionDiameter"] = str(pet.DataCollectionDiameter)
         # Number of Slices is avg. number slice?
         if hasattr(pet, 'NumberofSlices'):
             metadata["NumberofSlices"] = str(pet.NumberofSlices)

imgtools/modules/structureset.py

@@ -39,6 +39,10 @@ def from_dicom_rtstruct(cls, rtstruct_path: str) -> 'StructureSet':
         if hasattr(rtstruct, 'StructureSetROISequence'):
             metadata["numROIs"] = str(len(rtstruct.StructureSetROISequence))
 
+        if hasattr(rtstruct, 'BodyPartExamined'):
+            metadata["BodyPartExamined"] = str(rtstruct.BodyPartExamined)
+        if hasattr(rtstruct, 'DataCollectionDiameter'):
+            metadata["DataCollectionDiameter"] = str(rtstruct.DataCollectionDiameter)
         # Number of Slices is avg. number slice?
         if hasattr(rtstruct, 'NumberofSlices'):
             metadata["NumberofSlices"] = str(rtstruct.NumberofSlices)