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Bound-Aware Per-Organ Recall Risk Control for Multi-Organ CT Segmentation under Clinical Domain Shift

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The paper introduces a distribution‑free risk control method that provides organ‑specific recall guarantees for frozen segmentation models. It calibrates per‑organ thresholds on an AMOS‑trained nnU‑Net, audits transfer to RAOS, and estimates local re‑certification cost using case‑level voxel false‑negative rates. The study compares Risk‑Controlling Prediction Sets (RCPS) and Conformal Risk Control (CRC), noting that RCPS offers high‑probability control of population‑mean risk while CRC provides weaker expectation control, and evaluates the effectiveness of the Waudby‑Smith‑Ramdas betting bound versus Hoeffding‑Bentkus bounds for re‑certification of Tier‑1 organs.

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