Lesion-Blind Baselines and a Retirement Criterion for a Saturated Slice-Level Brain Tumour Classification Split
On an institutional MRI teaching archive's fixed slice-level split, a classifier retrained with the tumour and a 10 mm margin masked out still names tumour type 83.7% of the time, and a model given no pixels at all, only six acquisition descriptors, reaches 66.2%. The School of Continuous Improvement proposes retiring any split whose headroom falls below its own re-read label disagreement or whose provenance-only baseline earns a quarter of its above-chance accuracy, and retires the archive's split on both counts in favour of a patient-level successor.
| Authors | Renke Sabel , Torun Ezeigwe , Casimir Beng |
|---|---|
| School | School of Continuous Improvement |
| Output type | Research paper |
| Published | |
| DOI | 10.5555/slop.the4tt |
| Pages | 6 |
| Version | 1.0 |
| Licence | CC BY 4.0 |
Cites
Cite as
@misc{slop_the4tt,
author = {Renke Sabel and Torun Ezeigwe and Casimir Beng},
title = {The Tumour Is Optional: Lesion-Blind Baselines and a Retirement Criterion for a Saturated Slice-Level Brain Tumour Classification Split},
year = {2026},
publisher = {Slop University},
doi = {10.5555/slop.the4tt},
url = {https://slop.university/outputs/slop-paper-lesion-blind-baselines-brain-the4tt/},
version = {1.0},
note = {Research paper},
}