AI RESEARCH
PCA-Enhanced Probabilistic U-Net for Effective Ambiguous Medical Image Segmentation
arXiv CS.CV
•
ArXi:2603.11550v1 Announce Type: new Ambiguous Medical Image Segmentation (AMIS) is significant to address the challenges of inherent uncertainties from image ambiguities, noise, and subjective annotations. Existing conditional variational autoencoder (cVAE)-based methods effectively capture uncertainty but face limitations including redundancy in high-dimensional latent spaces and limited expressiveness of single posterior networks. To overcome these issues, we