Unifying Active Learning and Semi-Supervised Learning for Medical Image Segmentation

arXiv:2607.25014 · cs.CV, stat.ML · Submitted 2026-07-27 · Read on arXiv

Bahram Jafrasteh, Cheng Wan, Heejong Kim, Johannes C. Paetzold, Qingyu Zhao

cs.CV, stat.ML

Submitted: 2026-07-27

Code: https://github.com/BahramJafrasteh/Regal

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

Terminology

Consistency — 42× in this paper · explained in 3 episodes
Augmentation — 21× in this paper · explained in 2 episodes
Active Learning — 17× in this paper · explained in 6 episodes
Semi-supervised Learning — 11× in this paper · explained in 4 episodes
Core — 8× in this paper · explained in 2 episodes
Benchmark — 7× in this paper · explained in 2 episodes
Accuracy — 6× in this paper · explained in 1 episode
Anterior Stroma — 6× in this paper
Central Zone — 5× in this paper
Coherence — 5× in this paper · explained in 2 episodes
Objective Mismatch — 5× in this paper · explained in 2 episodes
Distillation — 4× in this paper · explained in 2 episodes
Peripheral Zone — 4× in this paper
Pseudo-labeling — 4× in this paper · explained in 3 episodes
White Matter — 4× in this paper
Adam — 3× in this paper · explained in 3 episodes
Contrastive Learning — 3× in this paper · explained in 9 episodes
Developing Human Connectome Project — 3× in this paper
Knowledge Distillation — 3× in this paper · explained in 15 episodes
Robustness — 3× in this paper · explained in 6 episodes
Transformer — 3× in this paper · explained in 2 episodes
Transition Zone — 3× in this paper
Active Semi-Supervised Learning — 2× in this paper
Bidirectional Copy-Paste — 2× in this paper
Cortical Grey Matter — 2× in this paper
Data Augmentation — 2× in this paper · explained in 10 episodes
Decoder — 2× in this paper · explained in 2 episodes
Failure Modes — 2× in this paper · explained in 3 episodes
Generalization — 2× in this paper · explained in 14 episodes
Hyperparameters — 2× in this paper · explained in 2 episodes
Loss Function — 2× in this paper · explained in 2 episodes
Multi-objective Optimization — 2× in this paper · explained in 5 episodes
Performance Gap — 2× in this paper · explained in 2 episodes
Pseudo-labels — 2× in this paper · explained in 2 episodes
Regularization — 2× in this paper · explained in 3 episodes
Representation Learning — 2× in this paper · explained in 3 episodes
Semantic Segmentation — 2× in this paper · explained in 3 episodes
Semi-Supervised Learning (SSL) — 2× in this paper · explained in 2 episodes
UMAP Projection — 2× in this paper · explained in 2 episodes
nnU-Net — 2× in this paper · explained in 2 episodes
Ablation — 1× in this paper · explained in 1 episode
Benchmarking — 1× in this paper · explained in 4 episodes
Calibration — 1× in this paper · explained in 9 episodes
Clarity — 1× in this paper · explained in 3 episodes
Clustering — 1× in this paper · explained in 2 episodes
Cold-Start Problem — 1× in this paper · explained in 2 episodes
Data Leakage — 1× in this paper · explained in 2 episodes
Deep Grey Matter — 1× in this paper
Embeddings — 1× in this paper · explained in 2 episodes
Evaluation Protocol — 1× in this paper · explained in 2 episodes
Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
Faithfulness — 1× in this paper · explained in 2 episodes
Fidelity — 1× in this paper · explained in 2 episodes
Human-in-the-loop — 1× in this paper · explained in 4 episodes
Latent Representation — 1× in this paper · explained in 2 episodes
Latent Representations — 1× in this paper · explained in 3 episodes
Latent Space — 1× in this paper · explained in 7 episodes
Learning Paradigms — 1× in this paper · explained in 2 episodes
Monte Carlo Dropout — 1× in this paper · explained in 3 episodes
Objective Function — 1× in this paper · explained in 2 episodes
Overfitting — 1× in this paper · explained in 2 episodes
Pairwise Comparisons — 1× in this paper · explained in 2 episodes
Persistent Homology — 1× in this paper · explained in 4 episodes
Total Variation — 1× in this paper
Transfer Learning — 1× in this paper · explained in 16 episodes
Transformers — 1× in this paper · explained in 2 episodes
Unified Framework — 1× in this paper · explained in 6 episodes

Sources

Adam: A Method for Stochastic Optimization

Terminology

Sources

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