1 citations · 1 across the 2 of their papers we have counts for
6 papers
Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation
Haoyue Li, Yifan Gao, Feng Yuan +2
Foundation models pre-trained on large-scale natural image datasets offer a powerful paradigm for medical image segmentation. However, effectively transferring their learned repres…
Camyla: Scaling Autonomous Research in Medical Image Segmentation
Yifan Gao, Haoyue Li, Feng Yuan +3
We present Camyla, a system for fully autonomous research within the scientific domain of medical image segmentation. Camyla transforms raw datasets into literature-grounded resear…
Med-K2N: Flexible K-to-N Modality Translation for Medical Image Synthesis
Feng Yuan, Yifan Gao, Yuehua Ye +2
Cross-modal medical image synthesis research focuses on reconstructing missing imaging modalities from available ones to support clinical diagnosis. Driven by clinical necessities…
SafeClick: Error-Tolerant Interactive Segmentation of Any Medical Volumes via Hierarchical Expert Consensus
Yifan Gao, Jiaxi Sheng, Wenbin Wu +5
Foundation models for volumetric medical image segmentation have emerged as powerful tools in clinical workflows, enabling radiologists to delineate regions of interest through int…
Beyond Pixel Agreement: Large Language Models as Clinical Guardrails for Reliable Medical Image Segmentation
Jiaxi Sheng, Leyi Yu, Haoyue Li +2
Evaluating AI-generated medical image segmentations for clinical acceptability poses a significant challenge, as traditional pixelagreement metrics often fail to capture true diagn…
WeGA: Weakly-Supervised Global-Local Affinity Learning Framework for Lymph Node Metastasis Prediction in Rectal Cancer
Yifan Gao, Yaoxian Dong, Wenbin Wu +5
Accurate lymph node metastasis (LNM) assessment in rectal cancer is essential for treatment planning, yet current MRI-based evaluation shows unsatisfactory accuracy, leading to sub…