dicom-series-to-volume
Used for converting one CT DICOM series folder to a HU NIfTI volume with affine evidence. Not for multi-frame DICOM or clinical use.
- License 许可
- Apache-2.0
- 最近更新
- 2026-11-02
- Stars
- ★ 0
- Forks
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01 前言 Front Matter
- name
- dicom-series-to-volume
- license
- Apache-2.0
- metadata
- { "tags": [ "MedTech", "DICOM", "NIfTI" ], "author": "NVIDIA MedTech Team" }
- description
- Used for converting one CT DICOM series folder to a HU NIfTI volume with affine evidence. Not for multi-frame DICOM or clinical use.
- allowed-tools
- Bash
02 资源文件 8
- 参考文档BENCHMARK.md4.2 KB
- 参考文档evals/evals.json1.5 KB
- 脚本fixtures/generate_fixtures.py5.6 KB
- 脚本scripts/series_to_volume.py9.1 KB
- 参考文档skill_manifest.yaml6.0 KB
- 参考文档skill-card.md3.7 KB
- 其他skill.oms.sig5.4 KB
- 参考文档validators/output_schema.json2.1 KB
03 SKILL.md 正文
dicom_series_to_volume
Purpose
- Used for converting one CT DICOM series folder to a HU NIfTI volume with affine evidence. Not for multi-frame DICOM or clinical use.
- Use the wrapper exactly as documented; do not replace the upstream entrypoint with a handwritten implementation.
- Manifest I/O: inputs are
dicom_dir; outputs arenifti_volumeandresult_json.
Instructions
- Read
skill_manifest.yamlbefore changing arguments, side effects, or validation gates. - Run
scripts/series_to_volume.pythrough the documented command below; keep outputs under a caller-provided run directory. - If a host agent exposes
run_script, userun_script("scripts/series_to_volume.py", args=[...]); otherwise run the Bash/Python command shown below. - Check the emitted JSON and the paired
dicom_volume_quality_v1verifier before treating the run as evidence.
Available Scripts
| Script | Purpose | Arguments |
|---|---|---|
scripts/series_to_volume.py |
Primary entrypoint declared by skill_manifest.yaml. | PATH_TO_DICOM_DIR [--output OUT.nii.gz] |
Prerequisites
- Runtime requirements: Python packages listed in
runtime.side_effects.pip_packages. - Run commands from the repository root unless an existing section below says otherwise.
Limitations
- Single-series only; multi-series input is rejected at preflight.
- Multi-frame DICOM (NumberOfFrames > 1 per file) not supported.
- Compressed transfer syntaxes (JPEG / JPEG2000 / RLE) not supported.
- No voxel reorientation. The affine is derived from DICOM headers and represented in NIfTI/RAS coordinates; a downstream gate (e.g. expected_axcodes) is expected to assert orientation before this volume is fed to a segmentation model.
- Not for clinical deployment, autonomous diagnosis, regulatory submission, production inference (use a vetted converter such as dcm2niix for that).
Troubleshooting
| Error | Cause | Fix |
|---|---|---|
| Missing dependency or import error | Runtime package drift from skill_manifest.yaml. |
Install the packages declared in the manifest or use the documented setup command. |
| Empty or schema-invalid output | Wrong input path, unsupported modality, or upstream failure. | Re-run with a known fixture and inspect the wrapper JSON plus stderr. |
| Validation gate failure | Output violated a declared engineering invariant. | Keep the failed evidence pack and use the gate message to repair inputs or wrapper code. |
Reads one DICOM series, sorts slices by ImagePositionPatient, applies
RescaleSlope and RescaleIntercept, builds an affine from orientation and
spacing tags, and writes a .nii.gz plus JSON summary.
python scripts/series_to_volume.py PATH_TO_DICOM_DIR --output PATH_TO_OUT.nii.gz
For a trusted run with the paired verifier:
python -m eval_engine.run_trusted skills/dicom-series-to-volume \
--fixture PATH_TO_DICOM_DIR \
--out runs/dicom_series_to_volume_trusted
Key output fields: n_slices, series_instance_uid, output.path,
output.shape, output.spacing, output.axcodes, output.affine,
hu_range, and runtime.conversion_seconds.
Scope limits: single-series CT only; no multi-frame DICOM, compressed transfer syntax handling, RT structure sets, auto-reorientation, or clinical use.
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