A Compact Multi Scale Attention CNN for Brain MRI Tumour Detection Under a Duplicate Aware Evaluation Protocol

The paper’s main contribution is a reproducible, leakage-aware evaluation protocol (content-hash deduplication of a public brain MRI dataset reducing 506 → 228 unique images, followed by stratified grouped 5-fold CV with inner validation for early stopping and single-use test folds) applied to a compact multi-scale channel-spatial attention network (MSCA-Net, 0.34 M parameters).
Under this rigorous protocol it reports realistic performance (~0.82 accuracy / ~0.89 AUC) that is statistically indistinguishable from a stronger ResNet-18 baseline, while Grad-CAM evidence shows some correct predictions rely on non-brain cues. The work therefore supplies a careful reference point and a caution against overly optimistic published numbers on this (and similar) small public collections rather than claiming architectural superiority.