Home/Healthcare/dicom-series-preflight
D

dicom-series-preflight

by @nvidiav
4.3(120)

Used for header-only preflight of a single DICOM series folder before conversion or inference. It automatically scans and outputs a JSON report with inventory, orientation axcodes, PHI flags, findings, and a verdict, helping medical AI developers validate DICOM data quality efficiently and avoid failures from anomalous data.

dicommedical-imagingpreflightdata-validationGitHub
Installation
npx skills add https://github.com/nvidia/skills --skill dicom-series-preflight
compare_arrows

Before / After Comparison

1 组
Before

Without this skill, developers had to manually inspect each DICOM file header for transfer syntax, orientation, PHI flags, etc., averaging about 60 minutes per series and often missing critical issues.

After

This skill automatically scans the entire series folder and generates a complete preflight JSON report in just 10 minutes, containing all necessary validation info and can be paired with a quality verifier for a trusted pack.

SKILL.md

DICOM Series Preflight

Purpose

  • Used for header-only preflight of one DICOM series folder before conversion or inference. Not for de-identification or clinical clearance.
  • Use the wrapper exactly as documented; do not replace the upstream entrypoint with a handwritten implementation.
  • Manifest I/O: inputs are dicom_dir; outputs are preflight_json.

Instructions

  • Read skill_manifest.yaml before changing arguments, side effects, or validation gates.
  • Run scripts/preflight_series.py through the documented command below; keep outputs under a caller-provided run directory.
  • If a host agent exposes run_script, use run_script("scripts/preflight_series.py", args=[...]); otherwise run the Bash/Python command shown below.
  • Check the emitted JSON and paired verifier guidance before treating the run as evidence.

Available Scripts

ScriptPurposeArguments
scripts/preflight_series.pyPrimary entrypoint declared by skill_manifest.yaml.PATH_TO_DICOM_DIR

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

  • Header-only; does not decode pixel data or detect burnt-in PHI.
  • Canonical orientation gate assumes LPS-derived CT axcodes L,P,S.
  • Compressed transfer syntax and multi-frame instances are warned, not decoded.
  • Single-directory scan; does not reconcile multiple studies in one tree.
  • Not for clinical deployment, regulatory de-identification, autonomous diagnosis, production ingestion without a vetted converter.

Troubleshooting

ErrorCauseFix
Missing dependency or import errorRuntime package drift from skill_manifest.yaml.Install the packages declared in the manifest or use the documented setup command.
Empty or schema-invalid outputWrong input path, unsupported modality, or upstream failure.Re-run with a known fixture and inspect the wrapper JSON plus stderr.
Validation gate failureOutput violated a declared engineering invariant.Keep the failed evidence pack and use the gate message to repair inputs or wrapper code.

Scans a DICOM directory (one series per folder) without decoding pixels. Emits JSON with inventory, orientation axcodes, PHI flags, findings, and a preflight.verdict of pass, warn, or fail.

python scripts/preflight_series.py PATH_TO_DICOM_DIR

Pair with verifiers/dicom_preflight_quality_v1 for a trusted preflight pack:

make run-trusted SKILL=dicom_series_preflight \
  FIXTURE=skills/dicom-series-preflight/fixtures/clean_no_phi \
  OUT=runs/dicom_preflight_demo

Flagship workflow:

make run-workflow \
  WORKFLOW=examples/workflows/dicom_preflight_gate.yaml \
  WORKFLOW_INPUT=skills/dicom-series-preflight/fixtures/clean_no_phi \
  WORKFLOW_OUT=runs/dicom_preflight_gate

Not for de-identification, private-tag review, or clinical clearance.

User Reviews (0)

Write a Review

Effect
Usability
Docs
Compatibility

No reviews yet

Statistics

Installs1.9K
Rating4.3 / 5.0
Version
Updated2026年9月24日
Comparisons1

User Rating

4.3(120)
5
37%
4
43%
3
13%
2
5%
1
2%

Rate this Skill

0.0

Compatible Platforms

🤖claude-code

Timeline

Created2026年7月26日
Last Updated2026年9月24日
🎁 Agent Knowledge Cards
Survey