normal-guidance-39dcd7c0·1 events·first seen Aliases: Normal Guidance
This paper addresses weakly supervised classification of 3D medical images where only volume-level binary labels are available. The authors identify that a simple center-focused baseline outperforms attention-based and transformer-based multiple instance learning (MIL) at slice-level classification across brain, thoracic, and abdominal CT datasets. They propose Normal Guidance, a regularization technique that constrains learned attention distributions to follow a bell-shaped curve, achieving superior slice-level localization over state-of-the-art MIL methods across datasets totaling over 4 million 2D slices.