85 citations · 98 across the 10 of their papers we have counts for
10 papers
Auditable agentic AI for evidence-grounded thyroid ultrasound diagnosis and reporting
Haifan Gong, Shiyu Chen, Bodong Wang +11
Thyroid ultrasound diagnosis requires coordinated lesion localization, measurement, risk stratification and reporting, yet most AI systems address these tasks in isolation and prov…
SAM3-UNet: Simplified Adaptation of Segment Anything Model 3
Xinyu Xiong, Zihuang Wu, Lei Lu +1
In this paper, we introduce SAM3-UNet, a simplified variant of Segment Anything Model 3 (SAM3), designed to adapt SAM3 for downstream tasks at a low cost. Our SAM3-UNet consists of…
SAM2-UNeXT: An Improved High-Resolution Baseline for Adapting Foundation Models to Downstream Segmentation Tasks
Xinyu Xiong, Zihuang Wu, Lei Zhang +3
Recent studies have highlighted the potential of adapting the Segment Anything Model (SAM) for various downstream tasks. However, constructing a more powerful and generalizable enc…
PDC-Net: Pattern Divide-and-Conquer Network for Pelvic Radiation Injury Segmentation
Xinyu Xiong, Wuteng Cao, Zihuang Wu +4
Accurate segmentation of Pelvic Radiation Injury (PRI) from Magnetic Resonance Images (MRI) is crucial for more precise prognosis assessment and the development of personalized tre…
SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation
Xinyu Xiong, Zihuang Wu, Shuangyi Tan +6
Image segmentation plays an important role in vision understanding. Recently, the emerging vision foundation models continuously achieved superior performance on various tasks. Fol…
TP-DRSeg: Improving Diabetic Retinopathy Lesion Segmentation with Explicit Text-Prompts Assisted SAM
Wenxue Li, Xinyu Xiong, Peng Xia +2
Recent advances in large foundation models, such as the Segment Anything Model (SAM), have demonstrated considerable promise across various tasks. Despite their progress, these mod…
AlignSAM: Aligning Segment Anything Model to Open Context via Reinforcement Learning
Duojun Huang, Xinyu Xiong, Jie Ma +4
Powered by massive curated training data, Segment Anything Model (SAM) has demonstrated its impressive generalization capabilities in open-world scenarios with the guidance of prom…
Annotation-Efficient Polyp Segmentation via Active Learning
Duojun Huang, Xinyu Xiong, De-Jun Fan +3
Deep learning-based techniques have proven effective in polyp segmentation tasks when provided with sufficient pixel-wise labeled data. However, the high cost of manual annotation…
Semi- and Weakly-Supervised Learning for Mammogram Mass Segmentation with Limited Annotations
Xinyu Xiong, Churan Wang, Wenxue Li +1
Accurate identification of breast masses is crucial in diagnosing breast cancer; however, it can be challenging due to their small size and being camouflaged in surrounding normal…
Long-term Wind Power Forecasting with Hierarchical Spatial-Temporal Transformer
Yang Zhang, Lingbo Liu, Xinyu Xiong +3
Wind power is attracting increasing attention around the world due to its renewable, pollution-free, and other advantages. However, safely and stably integrating the high permeabil…