AnoFPDM: Anomaly Segmentation with Forward Process of Diffusion Models for Brain MRI

arXiv:2404.15683v1 Announce Type: new
Abstract: Weakly-supervised diffusion models (DM) in anomaly segmentation, leveraging image-level labels, have attracted significant attention for their superior performance compared to unsupervised methods. It eliminates the need for pixel-level labels in training, offering a more cost-effective alternative to supervised methods. However, existing methods are not fully weakly-supervised because they heavily rely on costly pixel-level labels for hyperparameter tuning in inference. To tackle this challenge, we introduce Anomaly Segmentation with Forward Process of Diffusion Models (AnoFPDM), a …

abstract alternative anomaly arxiv attention brain cost cs.cv diffusion diffusion models however image labels mri performance pixel process segmentation training type unsupervised weakly-supervised