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+## README For **Dagster_Minimal_Mode**
+
+```markdown
+# Dagster Minimal Mode Project
+
+This project demonstrates the radiomics workflow in **Dagster Minimal Mode**.
+Minimal Mode is a lightweight configuration of Dagster, focusing on simplicity and reduced overhead.
+
+## Features
+- Minimal orchestration setup for radiomics extraction.
+- Direct execution of ops/assets without full Dagster deployment.
+- Simplified configuration for quick testing and prototyping.
+
+## Requirements
+- Python 3.10+
+- Dagster (minimal mode enabled)
+- SimpleITK
+- Pandas
+- PySERA
+
+Install dependencies:
+```bash
+pip install dagster simpleitk pandas pysera
+
+# Running:
+python radiuma_pipeline.py
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+from dagster import op
+import pysera
+
+@op
+def extract_features(inputs):
+    result = pysera.process_batch(
+        image_input="data/images/ourT1.nii.gz",
+        mask_input="data/masks/ourT1_mask.nii.gz",
+        output_path="artifacts"
+    )
+    return result
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+# ops_reader.py
+from dagster import op
+import os
+import pysera
+
+@op
+def read_images():
+    # Match Radiuma.exe by processing a single pair or a flat folder.
+    # Here we keep folders; PySERA will find matching pairs.
+    image_dir = "data/images"
+    mask_dir = "data/masks"
+    return {"image_dir": image_dir, "mask_dir": mask_dir}
+
+@op
+def extract_features(data):
+    # Exact PySERA config mirrored from Radiuma.exe logs
+    result = pysera.process_batch(
+        image_input=data["image_dir"],
+        mask_input=data["mask_dir"],
+        output_path="./artifacts/results",
+        # Core run behavior
+        enable_parallelism=False,
+        num_workers=1,
+        apply_preprocessing=True,
+        roi_selection_mode="per_region",
+        roi_num=2,
+        min_roi_volume=50,
+        feature_value_mode="REAL_VALUE",
+        # Feature scope
+        categories="diag,morph,glcm,glrlm,glszm,ngtdm,ngldm",
+        dimensions="1st,2D",
+        bin_size=25,
+        # Logging/report
+        report="info",
+        # Temp path (matching Radiuma.exe run)
+        temporary_files_path=r"C:\Users\Omen16\AppData\Local\ViSERA\res\memory\memmap\pysera_temp",
+        # IBSI-based parameters mirrored from Radiuma.exe
+        IBSI_based_parameters={
+            "radiomics_DataType": "CT",
+            "radiomics_DiscType": "FBS",
+            "radiomics_isScale": 0,
+            "radiomics_VoxInterp": "Nearest",
+            "radiomics_ROIInterp": "Nearest",
+            "radiomics_isotVoxSize": 1.0,
+            "radiomics_isotVoxSize2D": 2.0,
+            "radiomics_isIsot2D": 0,
+            "radiomics_isGLround": 0,
+            "radiomics_isReSegRng": 0,
+            "radiomics_isOutliers": 0,
+            "radiomics_isQuntzStat": 1,
+            "radiomics_ReSegIntrvl01": -1000,
+            "radiomics_ReSegIntrvl02": 400,
+            "radiomics_ROI_PV": 0.5,
+            "radiomics_qntz": "Uniform",
+            "radiomics_IVH_Type": 3,
+            "radiomics_IVH_DiscCont": 1,
+            "radiomics_IVH_binSize": 2.0,
+        },
+    )
+    return result
+
+@op
+def write_report(result):
+    os.makedirs("artifacts", exist_ok=True)
+    report_path = "artifacts/radiomics_batch_report_radiuma_match.txt"
+
+    with open(report_path, "w") as f:
+        f.write(f"Success: {result['success']}\n")
+        f.write(f"Processed files: {result['processed_files']}\n")
+        f.write(f"Processing time: {result['processing_time']:.2f} seconds\n")
+        f.write(f"Output path: {result['output_path']}\n")
+        f.write("Note: Excel with Radiomics_Features, Parameters, Report is saved in output_path.\n")
+
+    return report_path
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+from dagster import op
+
+@op
+def write_report(features):
+    with open("artifacts/final_report.txt", "w", encoding="utf-8") as f:
+        f.write("# Radiomics Report\n")
+        f.write(f"Extracted {len(features)} features\n")
+        for k, v in features.items():
+            f.write(f"{k},{v}\n")
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+# radiuma_pipeline.py
+from dagster import job
+from ops_reader import read_images, extract_features, write_report
+
+@job
+def radiuma_job():
+    result = extract_features(read_images())
+    write_report(result)
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+alembic==1.17.2
+annotated-types==0.7.0
+antlr4-python3-runtime==4.13.2
+anyio==4.12.0
+backoff==2.2.1
+certifi==2025.11.12
+charset-normalizer==3.4.4
+click==8.3.1
+colorama==0.4.6
+coloredlogs==14.0
+connected-components-3d==3.26.1
+dagit==1.12.6
+dagster==1.12.6
+dagster-graphql==1.12.6
+dagster-pipes==1.12.6
+dagster-webserver==1.12.6
+dagster_shared==1.12.6
+dataclasses==0.6
+docstring_parser==0.17.0
+et_xmlfile==2.0.0
+filelock==3.20.0
+fsspec==2025.12.0
+gql==3.5.3
+graphene==3.4.3
+graphql-core==3.2.6
+graphql-relay==3.2.0
+greenlet==3.3.0
+grpcio==1.76.0
+grpcio-health-checking==1.76.0
+h11==0.16.0
+httptools==0.7.1
+humanfriendly==10.0
+idna==3.11
+ImageIO==2.37.2
+Jinja2==3.1.6
+joblib==1.5.2
+lazy_loader==0.4
+Mako==1.3.10
+markdown-it-py==4.0.0
+MarkupSafe==3.0.3
+mdurl==0.1.2
+multidict==6.7.0
+networkx==3.6.1
+nibabel==5.3.3
+numpy==2.2.6
+opencv-python==4.12.0.88
+openpyxl==3.1.5
+packaging==25.0
+pandas==2.3.3
+pathlib_abc==0.5.2
+pillow==12.0.0
+platformdirs==4.5.1
+propcache==0.4.1
+protobuf==6.33.2
+psutil==7.1.3
+pydantic==2.12.5
+pydantic_core==2.41.5
+pydicom==3.0.1
+Pygments==2.19.2
+pynrrd==1.1.3
+pyreadline3==3.5.4
+pysera==2.1.5
+python-dateutil==2.9.0.post0
+python-dotenv==1.2.1
+pytz==2025.2
+pywin32==311
+PyYAML==6.0.3
+requests==2.32.5
+requests-toolbelt==1.0.0
+rich==14.2.0
+rt-utils==1.2.7
+scikit-image==0.25.2
+scikit-learn==1.8.0
+scipy==1.16.3
+setuptools==80.9.0
+simpleitk==2.5.3
+six==1.17.0
+SQLAlchemy==2.0.45
+starlette==0.50.0
+structlog==25.5.0
+tabulate==0.9.0
+threadpoolctl==3.6.0
+tifffile==2025.10.16
+tomli==2.3.0
+tomlkit==0.13.3
+toposort==1.10
+tqdm==4.67.1
+typing-inspection==0.4.2
+typing_extensions==4.15.0
+tzdata==2025.2
+universal_pathlib==0.3.7
+urllib3==2.6.2
+uvicorn==0.38.0
+watchdog==6.0.0
+watchfiles==1.1.1
+websockets==15.0.1
+yarl==1.22.0