Abstract Background and Objective Generalizable and trustworthy deep learning models for
PET/CT image segmentation necessitates large diverse multi-institutional datasets …

In recent years, deep learning models have shown their advantages in neuroimage
analysis, such as brain disease diagnosis. Unfortunately, it is usually difficult to acquire …

Disaster classification and victim detection are two important tasks in enabling efficient
rescue operations. In this paper, we propose a multi-task learning (MTL) model which …

Recently, federated learning has raised increasing interest in the medical image analysis
field due to its ability to aggregate multi-center data with privacy-preserving properties. A …

Objective. Both local and global context information is crucial semantic features for brain
tumor segmentation, while almost all the CNN-based methods cannot learn global spatial …