3 papers
cs.CV2026
Understanding From Human Perspective: A Multi-agent System for Interactive Egocentric Medical Image Segmentation
Rongjun Ge, Dongyang Wang, Heng Zhu +3
Interactive egocentric medical image segmentation (IEMIS) plays an important role in smart-glasses-assisted medical image review, segmenting the medical targets a clinician refers…
cs.CV2026
Personalized Longitudinal Medical Report Generation via Temporally-Aware Federated Adaptation
He Zhu, Ren Togo, Takahiro Ogawa +8
Longitudinal medical report generation is clinically important yet remains challenging due to strict privacy constraints and the evolving nature of disease progression. Although fe…
cs.CV2024
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering
He Zhu, Ren Togo, Takahiro Ogawa +1
Conventional medical artificial intelligence (AI) models face barriers in clinical application and ethical issues owing to their inability to handle the privacy-sensitive character…