MIRTO: a registration-gated, multiverse-tested evaluation protocol for unsupervised anomaly segmentation in brain MRI

arXiv:2610.02136 · cs.CV, cs.AI, eess.IV, physics.med-ph · Submitted 2026-10-01 · Read on arXiv

cs.CV, cs.AI, eess.IV, physics.med-ph

Submitted: 2026-10-01

Updated: 2026-10-01

Code: https://github.com/soumickmj/MIRTO

Terminology

• Aggregation — 52× in this paper · explained in 1 episode
• Calibration — 40× in this paper · explained in 7 episodes
• Hysteresis — 27× in this paper · explained in 3 episodes
• Pruning — 25× in this paper · explained in 4 episodes
• Diffusion Model — 18× in this paper · explained in 8 episodes
• Benchmark — 14× in this paper · explained in 2 episodes
• Diffusion Models — 12× in this paper · explained in 6 episodes
• Regret — 9× in this paper · explained in 3 episodes
• Rectified Flow — 5× in this paper · explained in 3 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Variational Bayes — 4× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 3× in this paper
• Conformal Prediction — 3× in this paper · explained in 5 episodes
• International Conference on Learning Representations — 3× in this paper
• Distillation — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Exchangeability — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Longitudinal Data — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Conformal Risk Control
• REFLECT: Rectified Flows for Efficient Brain Anomaly Correction Transport
• MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection
• Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection through Automatic Diffusion Models
• AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2
• Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection
• Denoising Diffusion Probabilistic Models
• Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection
• Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
• DINOv2: Learning Robust Visual Features without Supervision
• FiLM: Visual Reasoning with a General Conditioning Layer
• High-Resolution Image Synthesis with Latent Diffusion Models

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