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

arXiv 2608.18193 ↗First posted 18 Aug 2026cs.CV cs.AI cs.LGcited by 0

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Abstract (arXiv)

Distribution-free risk control adds organ-specific recall guarantees to frozen segmentation. We calibrate per-organ thresholds for an AMOS-trained nnU-Net, audit transfer to RAOS, and estimate local re-certification cost using case-level voxel false-negative rate (FNR). The AMOS control passes, but 7/12 organs exceed α=0.10 after transfer; smaller calibration sets can mask exceedances with conservative or vacuous thresholds. Risk-Controlling Prediction Sets (RCPS) give high-probability control of population-mean risk, whereas Conformal Risk Control (CRC) gives weaker expectation control. Both require exchangeability; fixed and global thresholds give no per-organ guarantee. The Waudby--Smith--Ramdas (WSR) betting bound re-certifies six Tier-1 organs with 25 local cases, versus 30--40 for Hoeffding--Bentkus (HB). CRC needs 10--15 but has a heavier individual-case tail. No Tier-2 organ meets our illustrative precision criterion with 25 cases.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 20 of its 25 references that are in the map. First posted on arXiv 18 Aug 2026.

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20 of 25 references.

References · 20

  1. 2016Distribution-Free Predictive Inference For Regressioncited by 668
  2. 2022TotalSegmentator: robust segmentation of 104 anatomical structures in CT imagescited by 613
  3. 2019Conformal Prediction Under Covariate Shiftcited by 519
  4. 2022Conformal prediction beyond exchangeabilitycited by 355
  5. 2022AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentationcited by 351
  6. 2022Conformal Risk Controlcited by 299
  7. 2021Distribution-Free, Risk-Controlling Prediction Setscited by 288
  8. 2021Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Controlcited by 271
  9. 2022Metrics reloaded: Recommendations for image analysis validationcited by 195
  10. 2020Estimating means of bounded random variables by bettingcited by 169
  11. 2019Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentationcited by 163
  12. 2021Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentationcited by 19
8 more
  1. 2024Rethinking Abdominal Organ Segmentation (RAOS) in the clinical scenario: A robustness evaluation benchmark with challenging casescited by 19
  2. 2025Conformal Prediction for Image Segmentation Using Morphological Prediction Setscited by 14
  3. 2024Conformal Performance Range Prediction for Segmentation Output Quality Controlcited by 8
  4. 2025Conformal Risk Control for Semantic Uncertainty Quantification in Computed Tomographycited by 8
  5. 2025Pitfalls of Conformal Predictions for Medical Image Classificationcited by 6
  6. 2025COMPASS: Robust Feature Conformal Prediction for Medical Segmentation Metricscited by 4
  7. 2023HALOS: Hallucination-free Organ Segmentation after Organ Resection Surgerycited by 3
  8. 2025Statistical Management of the False Discovery Rate in Medical Instance Segmentation Based on Conformal Risk Controlcited by 2

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