MIRTO: a registration-gated, multiverse-tested evaluation protocol for unsupervised anomaly segmentation in brain MRI
Paper recorded by Signals 4 on 2026-10-01 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-01 on arXiv · recorded by Signals 4 on 2026-10-02
Category: cs.AI · 人工智能 · first seen 2026-10-02
Abstract
Unsupervised anomaly detection (UAD) methods for brain MRI are ranked by a single score, yet that score rests on choices that are rarely reported: how each anomaly map is aligned with the reference, how and on which data the threshold is set, and which false-positive budget, metric, aggregation and lesion definition are used. We present MIRTO, an evaluation protocol that makes these choices explic
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Cite this page: MIRTO: a registration-gated, multiverse-tested evaluation protocol for unsupervised anomaly segmentation in brain MRI: the #17 most recent of 500 cs.AI papers we have recorded (as of 2026-10-01). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/mirto-a-registration-gated-multiverse-tested-evaluation-protocol-for-unsupervise.html
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