Abstract: Once deployed, medical image analysis methods are often faced with unexpected image corruptions and noise perturbations. These unknown covariate shifts present significant challenges to deep ...

As shown below, the inferred masks predicted by our segmentation model trained on the dataset appear similar to the ground truth masks, but they lack precision in certain areas. Concrete structures ...

Abstract: Convolutional Neural Networks (CNNs) dominate medical image classification, yet their “black box” nature limits understanding of their decision-making process. This study applies ...