completed the first version of dicom processing

pyalfe/containers.py

@@ -3,12 +3,18 @@
 
 from dependency_injector import containers, providers
 
-from pyalfe.data_structure import DefaultALFEDataDir, BIDSDataDir, Modality
+from pyalfe.data_structure import (
+    DefaultALFEDataDir,
+    BIDSDataDir,
+    PatientDicomDataDir,
+    Modality
+    )
 from pyalfe.image_processing import Convert3DProcessor, NilearnProcessor
 from pyalfe.image_registration import GreedyRegistration, AntsRegistration
 from pyalfe.inference import NNUnetV2
 from pyalfe.models import MODELS_PATH
-from pyalfe.pipeline import PyALFEPipelineRunner
+from pyalfe.pipeline import PyALFEPipelineRunner, DicomProcessingPipelineRunner
+from pyalfe.tasks.dicom_processing import DicomProcessing
 from pyalfe.tasks.initialization import Initialization
 from pyalfe.tasks.quantification import Quantification
 from pyalfe.tasks.registration import (
@@ -26,12 +32,11 @@
 from pyalfe.tasks.t1_preprocessing import T1Preprocessing
 
 
-class Container(containers.DeclarativeContainer):
+class PipelineContainer(containers.DeclarativeContainer):
     """
     container objects for all the dependencies of the pipeline.
     """
 
-    logger = logging.getLogger('Container')
     config = providers.Configuration()
 
     pipeline_dir = providers.Selector(
@@ -212,7 +217,7 @@ class Container(containers.DeclarativeContainer):
         dominant_tissue=config.options.dominant_tissue,
     )
 
-    pipeline_runner = providers.Singleton(
+    pyalfe_pipeline_runner = providers.Singleton(
         PyALFEPipelineRunner,
         initialization=initialization,
         skullstripping=skullstripping,
@@ -226,3 +231,40 @@ class Container(containers.DeclarativeContainer):
         resampling=resampling,
         quantification=quantification,
     )
+
+
+class DicomProcessingContianer(containers.DeclarativeContainer):
+    """Contianer for dicom processing pipeline depedencies"""
+
+    config = providers.Configuration()
+
+    pipeline_dir = providers.Selector(
+        config.options.data_dir_structure,
+        alfe=providers.Singleton(
+            DefaultALFEDataDir,
+            output_dir=os.devnull,
+            input_dir=config.options.input_dir,
+        ),
+        bids=providers.Singleton(
+            BIDSDataDir,
+            output_dir=os.devnull,
+            input_dir=config.options.input_dir,
+        ),
+    )
+
+    dicom_dir = providers.Singleton(
+        PatientDicomDataDir,
+        dicom_dir=config.options.dicom_dir
+    )
+
+    dicom_processing = providers.Singleton(
+        DicomProcessing,
+        pipeline_dir=pipeline_dir,
+        dicom_dir=dicom_dir,
+        overwrite=config.options.overwrite_images
+    )
+
+    dicom_processing_pipeline_runner = providers.Singleton(
+        DicomProcessingPipelineRunner,
+        dicom_processing=dicom_processing
+    )

pyalfe/data_structure.py

@@ -560,17 +560,17 @@ def get_quantification_file(
         return ret
 
 
-class PatientDicomDir():
+class PatientDicomDataDir():
     """This class is designe to work with directories containing raw dicom 
     files for a patient that are organized as:
     patient_id
-        └─ accession (study_id)
-            └─ series_id
+        └─ accession (study_uid)
+            └─ series_uid
                 ├─ instance_0.dcm
                 └─ instance_1.dcm
     """
-    def __init__(self, patient_dir) -> None:
-        self.patient_dir = patient_dir
+    def __init__(self, dicom_dir) -> None:
+        self.dicom_dir = dicom_dir
 
     def is_dicom_file(self, file):
         """Function to check if file is a dicom file.
@@ -623,19 +623,19 @@ def get_all_dicom_series_instances(self, accession):
             list of instances as values.
         """
         ret = {}
-        accession_path = os.path.join(self.patient_dir, accession)
-        for path in glob.glob(accession_path, '*'):
+        accession_path = os.path.join(self.dicom_dir, accession)
+        for path in glob.glob(os.path.join(accession_path, '*')):
             instances = []
-            for file in glob.glob(path, '*'):
+            for file in glob.glob(os.path.join(path, '*')):
                 if os.path.isfile(file) and self.is_dicom_file(file):
                     instances.append(file)
             if len(instances) > 0:
-                series_id = os.path.basename(path)
-                ret[series_id] = instances
+                series_uid = os.path.basename(path)
+                ret[series_uid] = instances
         return ret
 
 
-    def get_series(self, accession, series_id):
+    def get_series(self, accession, series_uid):
         """This method returns the path to a series.
         
         Parameters
@@ -644,12 +644,12 @@ def get_series(self, accession, series_id):
             The patient_id.
         accession: str
             The accession or study number.
-        series_id: str
+        series_uid: str
             The series ID.
 
         Returns
         -------
         str
         The path to the series directory
         """
-        return os.path.join(self.patient_dir, accession, series_id)
+        return os.path.join(self.dicom_dir, accession, series_uid)

pyalfe/main.py

@@ -90,6 +90,11 @@ def download(assets):
     '--data-dir-structure',
     type=click.Choice(['alfe', 'bids'], case_sensitive=False),
 )
+@click.option(
+    '-dcm',
+    '--dicom-dir',
+    type=click.Path(), default=None
+)
 def run(
     accession: str,
     config: str,
@@ -134,9 +139,9 @@ def run(
     -------
     None
     """
-    from pyalfe.containers import Container
+    from pyalfe.containers import PipelineContainer
 
-    container = Container()
+    container = PipelineContainer()
     container.config.from_ini(config, required=True, envs_required=True)
 
     options = container.config.options()
@@ -163,7 +168,7 @@ def run(
     click.echo(options)
 
     container.init_resources()
-    pipeline_runner = container.pipeline_runner()
+    pipeline_runner = container.pyalfe_pipeline_runner()
 
     pipeline_runner.run(accession)
 
@@ -234,5 +239,53 @@ def configure():
         config.write(conf)
 
 
+@main.command()
+@click.argument('accession')
+@click.argument('dicom_dir')
+@click.option(
+    '-c',
+    '--config',
+    default=DEFAULT_CFG,
+)
+@click.option('-nd', '--nifti-dir')
+@click.option(
+    '-dds',
+    '--data-dir-structure',
+    type=click.Choice(['alfe', 'bids'], case_sensitive=False),
+)
+@click.option('-ow/-now', '--overwrite/--no-overwrite', default=True)
+def process_dicom(
+    accession: str,
+    dicom_dir: str,
+    config: str,
+    nifti_dir: str,
+    data_dir_structure: str,
+    overwrite: bool,
+    ):
+    from pyalfe.containers import DicomProcessingContianer
+
+    container = DicomProcessingContianer()
+    container.config.from_ini(config, required=True, envs_required=True)
+
+    options = container.config.options()
+
+    options['dicom_dir'] = dicom_dir
+
+    if nifti_dir:    
+        options['nifti_dir'] = nifti_dir
+    else:
+        options['nifti_dir'] = options['input_dir']
+    if data_dir_structure:
+        options['data_dir_structure'] = data_dir_structure
+    options['overwrite_images'] = overwrite
+
+    container.init_resources()
+    pipeline_runner = container.dicom_processing_pipeline_runner()
+
+    pipeline_runner.run(accession)
+
+
+
+
 if __name__ == '__main__':
     main()

pyalfe/pipeline.py

@@ -1,3 +1,4 @@
+from pyalfe.tasks.dicom_processing import DicomProcessing
 from pyalfe.tasks.initialization import Initialization
 from pyalfe.tasks.quantification import Quantification
 from pyalfe.tasks.registration import (
@@ -14,7 +15,16 @@
 from pyalfe.tasks.t1_preprocessing import T1Preprocessing
 
 
-class PyALFEPipelineRunner:
+class PipelineRunner:
+    def __init__(self, steps):
+        self.steps = steps
+
+    def run(self, accession: str) -> None:
+        for step in self.steps:
+            step.run(accession)
+
+
+class PyALFEPipelineRunner(PipelineRunner):
     """The pyalfe pipeline runner.
 
     Attributes
@@ -57,27 +67,31 @@ def __init__(
         resampling: Resampling,
         quantification: Quantification,
     ):
-        self.initialization = initialization
-        self.skullstripping = skullstripping
-        self.t1_preprocessing = t1_preprocessing
-        self.cross_modality_registration = cross_modality_registration
-        self.flair_segmentation = flair_segmentation
-        self.enhancement_segmentation = enhancement_segmentation
-        self.tissue_segmentation = tissue_segmentation
-        self.t1_postprocessing = t1_postprocessing
-        self.t1_registration = t1_registration
-        self.resampling = resampling
-        self.quantification = quantification
+        steps = [
+            initialization,
+            skullstripping,
+            t1_preprocessing,
+            cross_modality_registration,
+            flair_segmentation,
+            enhancement_segmentation,
+            t1_postprocessing,
+            t1_registration,
+            tissue_segmentation,
+            resampling,
+            quantification
+        ]
+        super().__init__(steps)
+
+
 
-    def run(self, accession) -> None:
-        self.initialization.run(accession)
-        self.skullstripping.run(accession)
-        self.t1_preprocessing.run(accession)
-        self.cross_modality_registration.run(accession)
-        self.flair_segmentation.run(accession)
-        self.enhancement_segmentation.run(accession)
-        self.t1_postprocessing.run(accession)
-        self.t1_registration.run(accession)
-        self.tissue_segmentation.run(accession)
-        self.resampling.run(accession)
-        self.quantification.run(accession)
+class DicomProcessingPipelineRunner(PipelineRunner):
+    """The Dicom processing pipeline runner
+
+    Attributes
+    ----------
+    dicom_processing: DicomProcessing
+        The dicom processing object.
+    """
+    def __init__(self, dicom_processing: DicomProcessing):
+        steps = [dicom_processing]
+        super().__init__(steps)