Visual-language models have advanced the development of universal models, yet their application in medical imaging remains constrained by specific functional requirements and the limited data. Current general-purpose models are typically designed with task-specific branches and heads, which restrict...

Universal segmentation models offer significant potential in addressing a wide range of tasks by effectively leveraging discrete annotations. As the scope of tasks and modalities expands, it becomes increasingly important to generate and strategically position task- and modal-specific priors within ...

Medical images are regarded as important and sensitive data in the medical informatics systems. For transferring medical images over an insecure network, developing a secure encryption algorithm is necessary. Among the three main properties of security services (i.e., confidentiality, integrity, and...

Conventional medical image registration approaches directly optimize over the parameters of a transformation model. These approaches have been highly successful and are used generically for registrations of different anatomical regions. Recent deep registration networks are incredibly fast and accur...