PETDetectorEfficiencyOutlierChecker

FS — Functional Specification

1. Run PETDetectorEfficiencyOutlierChecker.exe in demonstration mode or with input.csv output.json arguments.
2. Read UTF-8 CSV and map columns to the data contract.
3. Convert values to the expected types and validate mandatory fields.
4. Perform calculations and rule checks for “PET Detector Efficiency Outlier Detection”.
5. Create individual checks and derive the overall status from the worst result.
6. Write machine-readable output.json; populate errors when a valid calculation cannot be produced.

input.csv example

ScannerID,CheckDate,TotalDetectors,MeanEfficiency,StdDevEfficiency,MinEfficiency,MaxEfficiency,DeadDetectorCount,NoisyDetectorCount,AffectedBlocks
PET-SIEMENS-01,2026-07-22,32768,1.0,0.02,0.92,1.08,0,0,""
PET-GE-02,2026-07-22,24576,1.0,0.05,0.15,1.20,3,2,"B12,B13,B45"
PET-PHILIPS-03,2026-07-22,28672,1.0,0.03,0.85,1.10,0,1,"B08"

Minimum output.json structure

{
  "utility": "PETDetectorEfficiencyOutlierChecker",
  "source": "input.csv",
  "status": "PASS|WARNING|FAIL",
  "derivedValues": {},
  "checks": [
    {
      "parameter": "example",
      "value": 0,
      "limit": "configured profile",
      "status": "PASS",
      "message": "criterion satisfied"
    }
  ],
  "errors": []
}

Minimum OQ scenarios

• A row within the approved profile shall return PASS.
• A non-critical limit violation shall return WARNING or a review status.
• A critical violation shall return FAIL or the applicable operational decision.
• A missing column, invalid type or impossible date shall populate errors and shall not return PASS.

Before operational use

• Reconcile formulas and limits with manufacturer documentation and the approved SOP.
• Fix the scanner model, software version and profile version.
• After an executable, formula or profile change, repeat affected tests.
• Retain the source CSV and JSON result together.