2 papers
cs.CV2024
MedSAM-U: Uncertainty-Guided Auto Multi-Prompt Adaptation for Reliable MedSAM
Nan Zhou, Ke Zou, Kai Ren +7
The Medical Segment Anything Model (MedSAM) has shown remarkable performance in medical image segmentation, drawing significant attention in the field. However, its sensitivity to…
cs.CV2024
Textual Inversion and Self-supervised Refinement for Radiology Report Generation
Yuanjiang Luo, Hongxiang Li, Xuan Wu +6
Existing mainstream approaches follow the encoder-decoder paradigm for generating radiology reports. They focus on improving the network structure of encoders and decoders, which l…