From Human Corrections to Learned Segmentations: A Critical Mathematical Review of Information, Learning, and Human Effort

cs.LG

Submitted: 2026-10-14

Updated: 2026-10-14

Comments: 40 pages, literature-selection and search record included

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• CASC-AI: Consensus-aware Self-corrective Learning for Noise Cell Segmentation
• Rethinking Convergence in Deep Learning: The Predictive-Corrective Paradigm for Anatomy-Informed Brain MRI Segmentation
• RAIL: Region-Aware Instructive Learning for Semi-Supervised Tooth Segmentation in CBCT
• Towards Clinician-Preferred Segmentation: Leveraging Human-in-the-Loop for Test Time Adaptation in Medical Image Segmentation
• Active Learning for Efficient Annotation of Surgical Videos with Weak Supervision
• Explainable Human-in-the-Loop Segmentation via Critic Feedback Signals
• MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance
• You Point, I Learn: Online Adaptation of Interactive Segmentation Models for Handling Distribution Shifts in Medical Imaging
• Bayesian Active Learning for Classification and Preference Learning
• An Overview of Machine Teaching

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