26 citations · 50 across the 17 of their papers we have counts for
10 papers · 1 filter
Self-correction Optimization for Interleaved Multimodal Generation
Xin You, Zhiwei Ning, Zukai Chen +7
Multimodal large language models (MLLMs) have made significant progress in visual understanding and generation. However, generating interleaved image--text content remains challeng…
Separating Capability from Confidence: Grounded Dual-State Calibration for GRPO-Trained Medical Vision-Language Models
Yangyang Xie, Ke Hao, Jiaqi Liu +2
Medical vision-language models (VLMs) require confidence that reflects both answer correctness and patient-specific visual evidence. Recent GRPO-based methods optimize verbalized c…
Towards Physics-Faithful Generation of Scientific Diagrams
Minghui Zhang, Jinxin Shi, Yifan Chang +12
Text-to-image generation has reached photorealistic quality, yet state-of-the-art systems remain unreliable at producing scientific diagrams, whose value depends not on appearance…
Towards Voxel Spacing Consistency for Medical Image Segmentation
Xin You, Runze Yang, Minghui Zhang +6
Volumetric medical image segmentation is essential for both preoperative diagnosis and intraoperative guidance. While recent years have witnessed rapid progress in segmentation arc…
TopoVST: Toward Topology-fidelitous Vessel Skeleton Tracking
Yaoyu Liu, Minghui Zhang, Junjun He +1
Automatic extraction of vessel skeletons is crucial for many clinical applications. However, achieving topologically faithful delineation of thin vessel skeletons remains highly ch…
TubeMLLM: A Foundation Model for Topology Knowledge Exploration in Vessel-like Anatomy
Yaoyu Liu, Minghui Zhang, Xin You +2
Modeling medical vessel-like anatomy is challenging due to its intricate topology and sensitivity to dataset shifts. Consequently, task-specific models often suffer from topologica…
U-VLM: Hierarchical Vision Language Modeling for Report Generation
Pengcheng Shi, Minghui Zhang, Kehan Song +3
Automated radiology report generation is key for reducing radiologist workload and improving diagnostic consistency, yet generating accurate reports for 3D medical imaging remains…
LNQ 2023 challenge: Benchmark of weakly-supervised techniques for mediastinal lymph node quantification
Reuben Dorent, Roya Khajavi, Tagwa Idris +24
Accurate assessment of lymph node size in 3D CT scans is crucial for cancer staging, therapeutic management, and monitoring treatment response. Existing state-of-the-art segmentati…
PnPNet: Pull-and-Push Networks for Volumetric Segmentation with Boundary Confusion
Xin You, Ming Ding, Minghui Zhang +4
Precise boundary segmentation of volumetric images is a critical task for image-guided diagnosis and computer-assisted intervention, especially for boundary confusion in clinical p…
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to influence the risk, severity, an…