8 citations · 12 across the 5 of their papers we have counts for
5 papers
SynerMedGen: Synergizing Medical Multimodal Understanding with Generation via Task Alignment
Weiren Zhao, Yi Dong, Cheng Chen
Unifying multimodal understanding and generation is a compelling frontier that is beginning to emerge in the medical field. However, the limited existing unified medical models typ…
EchoFM: Foundation Model for Generalizable Echocardiogram Analysis
Sekeun Kim, Pengfei Jin, Sifan Song +6
Foundation models have recently gained significant attention because of their generalizability and adaptability across multiple tasks and data distributions. Although medical found…
Beyond Adapter Retrieval: Latent Geometry-Preserving Composition via Sparse Task Projection
Pengfei Jin, Peng Shu, Sifan Song +6
Recent advances in parameter-efficient transfer learning have demonstrated the utility of composing LoRA adapters from libraries of pretrained modules. However, most existing appro…
MA-SAM: Modality-agnostic SAM Adaptation for 3D Medical Image Segmentation
Cheng Chen, Juzheng Miao, Dufan Wu +10
The Segment Anything Model (SAM), a foundation model for general image segmentation, has demonstrated impressive zero-shot performance across numerous natural image segmentation ta…
MediViSTA: Medical Video Segmentation via Temporal Fusion SAM Adaptation for Echocardiography
Sekeun Kim, Pengfei Jin, Cheng Chen +9
Despite achieving impressive results in general-purpose semantic segmentation with strong generalization on natural images, the Segment Anything Model (SAM) has shown less precisio…