7 citations · 24 across the 16 of their papers we have counts for
18 papers
3DMedAgent: Unified Perception-to-Understanding for 3D Medical Analysis
Ziyue Wang, Linghan Cai, Chang Han Low +8
3D CT analysis spans a continuum from low-level perception to high-level clinical understanding. Existing 3D-oriented analysis methods adopt either isolated task-specific modeling…
MedOpenClaw and MedFlowBench: Auditing Medical Agents in Full-Study Workflows
Weixiang Shen, Chengzhi Shen, Yanzhu Hu +12
Medical imaging benchmarks often evaluate VLMs on pre-selected 2D images, slices, crops, or patches, making evaluation closer to visual recognition. Real clinical workflows impose…
OPGAgent: An Agent for Auditable Dental Panoramic X-ray Interpretation
Zhaolin Yu, Litao Yang, Ben Babicka +7
Orthopantomograms (OPGs) are the standard panoramic radiograph in dentistry, used for full-arch screening across multiple diagnostic tasks. While Vision Language Models (VLMs) now…
SWE Context Bench: A Benchmark for Context Learning in Coding
Jiayuan Zhu, Junde Wu, Minhao Hu +9
Large language models are increasingly used as coding agents for software engineering tasks. Current benchmarks mainly evaluate whether the agent can correctly solve the request or…
SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking
Haofeng Liu, Ziyue Wang, Sudhanshu Mishra +8
Surgical scene understanding demands temporally consistent tracking of instruments and tissues. For clinical use, such tracking should generalize to new centers and procedure types…
MediRound: Multi-Round Entity-Level Reasoning Segmentation in Medical Images
Qinyue Tong, Ziqian Lu, Jun Liu +3
Despite notable progress in text-guided medical image segmentation nowadays, these methods are limited to single-round dialogues and fail to support multi-round reasoning, which is…
Git Context Controller: Manage the Context of LLM-based Agents like Git
Junde Wu, Minhao Hu, Jiayuan Zhu +4
Large language model (LLM) agents have demonstrated strong capabilities in long-horizon tasks by interleaving reasoning with tool use. However, as these agents scale to complex wor…
Structure Matters: Revisiting Boundary Refinement in Video Object Segmentation
Guanyi Qin, Ziyue Wang, Daiyun Shen +5
Given an object mask, Semi-supervised Video Object Segmentation (SVOS) technique aims to track and segment the object across video frames, serving as a fundamental task in computer…
SurgVLM: A Large Vision-Language Model and Systematic Evaluation Benchmark for Surgical Intelligence
Zhitao Zeng, Zhu Zhuo, Xiaojun Jia +12
Foundation models have achieved transformative success across biomedical domains by enabling holistic understanding of multimodal data. However, their application in surgery remain…
ReSurgSAM2: Referring Segment Anything in Surgical Video via Credible Long-term Tracking
Haofeng Liu, Mingqi Gao, Xuxiao Luo +4
Surgical scene segmentation is critical in computer-assisted surgery and is vital for enhancing surgical quality and patient outcomes. Recently, referring surgical segmentation is…
MedAgent-Pro: Towards Evidence-based Multi-modal Medical Diagnosis via Reasoning Agentic Workflow
Ziyue Wang, Junde Wu, Linghan Cai +4
In modern medicine, clinical diagnosis relies on the comprehensive analysis of primarily textual and visual data, drawing on medical expertise to ensure systematic and rigorous rea…
Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic Tools
Junde Wu, Jiayuan Zhu, Yuyuan Liu +2
We introduce Agentic Reasoning, a framework that enhances large language model (LLM) reasoning by integrating external tool-using agents. Agentic Reasoning dynamically leverages we…
HCL-Diff: Hybrid conditional latent diffusion with high frequency enhancement for CBCT-to-CT synthesis
Shi Yin, Hongqi Tan, Li Ming Chong +6
Background: Cone-beam computed tomography (CBCT) plays a crucial role in image-guided radiotherapy, but artifacts and noise make them unsuitable for accurate dose calculation. Arti…
Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning
Haofeng Liu, Erli Zhang, Junde Wu +2
Surgical video segmentation is a critical task in computer-assisted surgery and is vital for enhancing surgical quality and patient outcomes. Recently, the Segment Anything Model 2…
MGI: Multimodal Contrastive pre-training of Genomic and Medical Imaging
Jiaying Zhou, Mingzhou Jiang, Junde Wu +3
Medicine is inherently a multimodal discipline. Medical images can reflect the pathological changes of cancer and tumors, while the expression of specific genes can influence their…
Not just Birds and Cars: Generic, Scalable and Explainable Models for Professional Visual Recognition
Junde Wu, Jiayuan Zhu, Min Xu +1
Some visual recognition tasks are more challenging then the general ones as they require professional categories of images. The previous efforts, like fine-grained vision classific…
Towards Collective Intelligence: Uncertainty-aware SAM Adaptation for Ambiguous Medical Image Segmentation
Mingzhou Jiang, Jiaying Zhou, Junde Wu +3
Collective intelligence from multiple medical experts consistently surpasses individual expertise in clinical diagnosis, particularly for ambiguous medical image segmentation tasks…
One-Prompt to Segment All Medical Images
Junde Wu, Jiayuan Zhu, Yueming Jin +1
Large foundation models, known for their strong zero-shot generalization, have excelled in visual and language applications. However, applying them to medical image segmentation, a…