ct-segmentation-quality-v1

name	ct-segmentation-quality-v1
description	Audits nv_segment_ct evidence packs for label-map readability, anatomy plausibility (organ volume bounds, fragmentation, bilateral symmetry, liver-larger-than-spleen), and optional per-class Dice/IoU against a referenced ground-truth label map. Engineering verification only.
license	Apache-2.0

ct_segmentation_quality_v1

Purpose

• Audits nv_segment_ct evidence packs for label-map readability, anatomy plausibility, requested-label containment, and optional Dice/IoU against a recorded ground-truth label map.
• Use this after the source segmentation skill has produced an evidence pack. Engineering verification only.
• Manifest I/O: inputs are nv_segment_ct_evidence_pack; outputs are ct_segmentation_quality_report.

Instructions

• Run scripts/grade.py on the evidence-pack directory that should be audited.
• If a host agent exposes run_script, use run_script("scripts/grade.py", args=["RUNS/PACK_DIR"]).
• Prefer the eval-engine command when you need a verifier evidence pack; use the direct Python command for quick local inspection.

Available Scripts

Script	Purpose	Arguments
scripts/grade.py	Primary verifier entrypoint declared by skill_manifest.yaml.	EVIDENCE_PACK_DIR

Prerequisites

• The target pack must contain manifest.json, validation_summary.json, and output.json.
• The label-map path recorded in output.path must resolve from the pack directory or current repo root.

Limitations

• Single-pack verifier only; dataset-level aggregation belongs in benchmarks/.
• Anatomy bounds are engineering floors and may fail pediatric, post-resection, or pathological cases intentionally.
• Not for clinical interpretation.

Troubleshooting

Error	Cause	Fix
Missing pack files	The fixture path is not an evidence-pack directory.	Point the verifier at the completed source-skill run directory.
Label map unreadable	output.path is missing or stale.	Preserve source-skill artifacts with the evidence pack before auditing.
Plausibility failure	Output violates an engineering floor.	Keep the failed verifier output and inspect per-tier reasons.

Paired verifier for skills/nv-segment-ct.

python eval_engine/run.py verifiers/ct_segmentation_quality_v1 \
  --fixture runs/spleen_clean \
  --out runs/spleen_clean_quality

The verifier reads the target pack's manifest.json, validation_summary.json, and output.json. It loads the label-map NIfTI referenced at output.path, recomputes per-class voxel counts and converts to volumes using the recorded spacing. It then runs three tiers:

• artifact_inventory — label-map file exists, integer dtype, shape and affine match the recorded input geometry.
• anatomy_plausibility — per-class volume bounds (e.g. spleen 50-500 mL), largest connected component dominates, fragmentation cap, bilateral organ symmetry, and liver_volume > spleen_volume when both are present.
• gt_metrics — runs only if input.ground_truth_path is recorded in the evidence pack and the file is readable. Computes per-class Dice and IoU against the reference and checks per-class Dice floors.

Per-class anatomy bounds live in validators/anatomy_bounds.json. Bounds are population-typical adult ranges; pediatric or post-resection cases will fail intentionally for v0.1.

This is a single-pack verifier. Dataset-level aggregation (mean Dice across N cases) belongs in benchmarks/.

Not for clinical interpretation.