Improve functionality to organize long lists of DICOM data into patient, cycle, timepoint

docs/source/tutorials/dicom_organization/dicom_organization.rst

@@ -0,0 +1,178 @@
+DICOM File Organization
+=======================
+
+PyTheranostics provides utilities to organize DICOM files into a structured format suitable for dosimetry workflows. The ``dicom_organizer`` module can process folders of DICOM files and automatically organize them by patient, cycle, and timepoint.
+
+Overview
+--------
+
+The organizer handles:
+
+* **Multiple patients** in a single folder
+* **Multiple imaging cycles** per patient (e.g., therapy cycles separated by weeks)
+* **Multiple timepoints** per cycle (e.g., scans at different times during a cycle)
+* **Mixed modalities** (CT, SPECT/NM, PET, RTSTRUCT)
+* **Same-day acquisitions** at different times (using datetime-based splitting)
+
+Output structure
+----------------
+
+The organizer creates a hierarchical folder structure::
+
+    PatientID/
+        Cycle1/
+            tp1/
+                CT/
+                    *.dcm
+                SPECT/
+                    *.dcm
+                CT/
+                    RTstruct/
+                        *.dcm
+            tp2/
+                CT/
+                SPECT/
+        Cycle2/
+            tp1/
+                ...
+
+Basic Usage
+-----------
+
+Organize all DICOM files in a folder
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+    from pytheranostics.dicomtools import organize_folder_by_cycles
+
+    # Organize all patients in a folder
+    result = organize_folder_by_cycles(
+        storage_root="/path/to/dicom/files",
+        output_base="/path/to/organized/output",
+        cycle_gap_days=15,              # New cycle if gap >= 15 days
+        timepoint_separation_days=1,    # New timepoint if gap >= 1 day
+        move=True                        # Move files (False to copy)
+    )
+
+    # Result is a dict: {PatientID: {CycleX: {tpY: [Path, ...]}}}
+    print(result)
+
+Organize specific patients only
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. code-block:: python
+
+    # Filter to specific patient IDs
+    result = organize_folder_by_cycles(
+        storage_root="/path/to/dicom/files",
+        output_base="/path/to/organized/output",
+        patient_id_filter=["PATIENT001", "PATIENT002"]
+    )
+
+Handle same-day acquisitions
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+For protocols with multiple scans on the same day (e.g., morning CT and afternoon SPECT+CT), use fractional days to separate timepoints based on actual acquisition times:
+
+.. code-block:: python
+
+    # Separate timepoints if acquisition times differ by >= 4.8 hours
+    result = organize_folder_by_cycles(
+        storage_root="/path/to/dicom/files",
+        output_base="/path/to/organized/output",
+        timepoint_separation_days=0.2  # 0.2 days ≈ 4.8 hours
+    )
+
+This uses ``AcquisitionDateTime`` from DICOM tags (or file modification time as fallback) to split same-day scans into separate timepoints.
+
+Debugging and Inspection
+-------------------------
+
+Use ``summarize_timepoints()`` to inspect detected series before organizing:
+
+.. code-block:: python
+
+    from pytheranostics.dicomtools import summarize_timepoints
+
+    # Get summary of all detected series
+    summary = summarize_timepoints(
+        storage_root="/path/to/dicom/files",
+        patient_id_filter=["PATIENT001"]
+    )
+
+    # Summary shows: study_date, modality, series_number, datetime, and gaps
+    for patient_id, entries in summary.items():
+        print(f"\n{patient_id}:")
+        for entry in entries:
+            print(f"  {entry['study_date']} - {entry['modality']} "
+                  f"Series{entry['series_number']} at {entry['datetime']} "
+                  f"(gap: {entry['delta_hours']:.1f}h)")
+
+Example output::
+
+    PATIENT001:
+      20190409 - CT Series2 at 2019-04-09 11:34:57 (gap: None)
+      20190409 - NM Series5 at 2019-04-09 16:06:50 (gap: 4.5h)
+      20190409 - CT Series2 at 2019-04-09 16:26:59 (gap: 0.3h)
+      20190410 - CT Series2 at 2019-04-10 10:15:23 (gap: 17.8h)
+      20190413 - NM Series4 at 2019-04-13 14:22:10 (gap: 76.1h)
+
+This helps diagnose issues like:
+
+* Missing timepoints
+* Incorrectly merged same-day scans
+* Unexpected gaps between acquisitions
+
+Parameters Reference
+--------------------
+
+``organize_folder_by_cycles()``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+:storage_root: Root directory to scan recursively for ``.dcm`` files
+:output_base: Base directory for organized output (defaults to ``storage_root``)
+:cycle_gap_days: Gap threshold (days) to start a new cycle (default: 15)
+:timepoint_separation_days: Gap threshold (days) to start a new timepoint within a cycle (default: 1, can be fractional like 0.1 for 2.4 hours)
+:move: If ``True``, move files; if ``False``, copy files (default: ``True``)
+:patient_id_filter: List of PatientIDs to process; if ``None``, process all (default: ``None``)
+
+Returns a nested dictionary: ``{PatientID: {"CycleX": {"tpY": [Path, ...]}}}}``
+
+``summarize_timepoints()``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+:storage_root: Root directory to scan for DICOM files
+:patient_id_filter: Optional list of PatientIDs to summarize
+
+Returns: ``{PatientID: [{study_date, modality, series_number, datetime, delta_hours}, ...]}``
+
+Advanced: Integration with DICOM Receiver
+------------------------------------------
+
+The organizer can be triggered automatically after receiving DICOM files via C-STORE:
+
+.. code-block:: python
+
+    from pytheranostics.dicomtools.dicom_receiver import DICOMReceiver
+
+    receiver = DICOMReceiver(
+        ae_title="PYTHERANOSTICS",
+        port=11112,
+        storage_root="/path/to/storage",
+        auto_organize=True,                            # Enable auto-organize
+        auto_organize_output_base="/path/to/organized",
+        auto_organize_cycle_gap_days=15,
+        auto_organize_timepoint_separation_days=0.2,   # 4.8 hours
+        auto_organize_debounce_seconds=60              # Wait 60s after last file
+    )
+
+    receiver.start()
+
+The receiver will automatically call ``organize_folder_by_cycles()`` 60 seconds after the last DICOM file is received for each patient.
+
+See Also
+--------
+
+* :doc:`../Data_Ingestion_Examples/Data_Ingestion_Examples` - General data ingestion workflows
+* :doc:`../getting_started/project_setup_tutorial` - Initial project setup

docs/source/tutorials/index.rst

@@ -7,7 +7,8 @@ Hands-on walkthroughs that demonstrate common PyTheranostics workflows.
    :maxdepth: 1
 
    getting_started/project_setup_tutorial
+   dicom_organization/dicom_organization
+   Data_Ingestion_Examples/Data_Ingestion_Examples
    segmentation/total_segmentator_tutorial
    SPECT2SUV/SPECT2SUV
    ROI_Mapping_Tutorial/ROI_Mapping_Tutorial
-   Data_Ingestion_Examples/Data_Ingestion_Examples

pytheranostics/dicomtools/__init__.py

@@ -1 +1,8 @@
 """DICOM utilities exposed at the package level."""
+
+from .dicom_organizer import organize_folder_by_cycles, summarize_timepoints
+
+__all__ = [
+    "organize_folder_by_cycles",
+    "summarize_timepoints",
+]