3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.CV2024
SAMCT: Segment Any CT Allowing Labor-Free Task-Indicator Prompts
Xian Lin, Yangyang Xiang, Zhehao Wang +3
Segment anything model (SAM), a foundation model with superior versatility and generalization across diverse segmentation tasks, has attracted widespread attention in medical imagi…
eess.IV2023★ 3 cited
ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation
Xian Lin, Zengqiang Yan, Xianbo Deng +2
Transformers have been extensively studied in medical image segmentation to build pairwise long-range dependence. Yet, relatively limited well-annotated medical image data makes tr…
cs.CV2023
Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting
Xian Lin, Yangyang Xiang, Li Yu +1
End-to-end medical image segmentation is of great value for computer-aided diagnosis dominated by task-specific models, usually suffering from poor generalization. With recent brea…