1 citations · 1 across the 10 of their papers we have counts for
11 papers
Sivia: Learning to Draw, Learning to Learn
Feng Yuan, Yifan Gao, Xinyi Gao +5
A paper's overview figure is often the first thing readers see: it must explain the method correctly and look polished. We present Sivia, an overview-figure system that reads the p…
Anatomy-Guided Residual Motion Diffusion for Controllable 4D Cardiac MRI Synthesis
Yiheng Cao, Gustavo Andrade-Miranda, Jiatian Zhang +2
Developing robust artificial intelligence models for 4D (3D + time) medical imaging is constrained by limited annotated data, inter-device domain shifts, and privacy restrictions.…
Temporally Consistent and Controllable Video Generation of 2D Cine CMR via Latent Space Motion Modeling
Yiheng Cao, Gustavo Andrade-Miranda, Jiatian Zhang +2
Cine cardiac magnetic resonance is the gold standard for assessing cardiac function, but the scarcity of public datasets limits the development of advanced data-driven models. To a…
GIFT: Global Irreplaceability Frame Targeting for Efficient Video Understanding
Junpeng Ma, Sashuai Zhou, Guanghao Li +9
Video Large Language Models (VLMs) have achieved remarkable success in video understanding, but the significant computational cost from processing dense frames severely limits thei…
Colon-Bench: An Agentic Workflow for Scalable Dense Lesion Annotation in Full-Procedure Colonoscopy Videos
Abdullah Hamdi, Changchun Yang, Xin Gao
Early screening via colonoscopy is critical for colon cancer prevention, yet developing robust AI systems for this domain is hindered by the lack of densely annotated, long-sequenc…
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…
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…
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…
FermatSyn: SAM2-Enhanced Bidirectional Mamba with Isotropic Spiral Scanning for Multi-Modal Medical Image Synthesis
Feng Yuan, Yifan Gao, Haoyue Li +1
Multi-modal medical image synthesis is pivotal for alleviating clinical data scarcity, yet existing methods fail to reconcile global anatomical consistency with high-fidelity local…