7 papers
ConRad: Efficient Conformal Prediction for Radiomics
Matt Y. Cheung, Ashok Veeraraghavan, Guha Balakrishnan
Radiomic features derived from medical images and segmentation masks are used to support decision making in clinical imaging pipelines. In practice, these features are often comput…
Conformal Certification of Reasoning Trace Prefixes
Matt Y. Cheung, Ashok Veeraraghavan, Hanjie Chen +1
Language model reasoning traces are rarely all-or-nothing; they frequently contain valid intermediate steps before a critical error occurs. Existing uncertainty quantification meth…
Efficient Conformal Volumetry for Template-Based Segmentation
Matt Y. Cheung, Ashok Veeraraghavan, Guha Balakrishnan
Template-based segmentation, a widely used paradigm in medical imaging, propagates anatomical labels via deformable registration from a labeled atlas to a target image, and is ofte…
COMPASS: Robust Feature Conformal Prediction for Medical Segmentation Metrics
Matt Y. Cheung, Ashok Veeraraghavan, Guha Balakrishnan
In clinical applications, the utility of segmentation models is often based on the accuracy of derived downstream metrics such as organ size, rather than by the pixel-level accurac…
Bias-Aware Conformal Prediction for Metric-Based Imaging Pipelines
Matt Y. Cheung, Tucker J. Netherton, Laurence E. Court +2
Reliable confidence measures of metrics derived from medical imaging reconstruction pipelines would improve the standard of decision-making in many clinical workflows. Conformal Pr…
Metric-Guided Conformal Bounds for Probabilistic Image Reconstruction
Matt Y Cheung, Tucker J Netherton, Laurence E Court +2
Modern deep learning reconstruction algorithms generate impressively realistic scans from sparse inputs, but can often produce significant inaccuracies. This makes it difficult to…