Acquisition parameters like kernel and noise produce axis-specific effects on lung-nodule AI (measurement vs detection) that a 4-feature pixel fingerprint can recover even when DICOM metadata cannot.
ACR’s Assess-AI: a registry for real-world performance monitoring of clinical imaging artificial intelligence.J Am Coll Radiol
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Acquisition state behaves as a structured, measurable variable governing lung-nodule AI: kernel-driven measurement instability and noise-driven detection fragility, invisible to DICOM metadata
Acquisition parameters like kernel and noise produce axis-specific effects on lung-nodule AI (measurement vs detection) that a 4-feature pixel fingerprint can recover even when DICOM metadata cannot.