activity
20242026
collaborators

7 papers

cs.CV2026

Enhancing Brain MRI Anomaly Detection and Reasoning with ROI Rethink and Synthetic Data

Shangkun Li, Jie Xu, Yi Guo +2

Medical vision-language models typically generate diagnoses through single-pass inference without indicating which image regions support their conclusions. This lack of spatial gro…

cs.CV2026

DepthPilot: From Controllability to Interpretability in Colonoscopy Video Generation

Junhu Fu, Ke Chen, Weidong Guo +9

Controllable medical video generation has achieved remarkable progress, but it still lacks interpretability, which requires the alignment of generated contents with physical priors…

cs.CV2026

Unified Ultrasound Intelligence Toward an End-to-End Agentic System

Chen Ma, Yunshu Li, Junhu Fu +3

Clinical ultrasound analysis demands models that generalize across heterogeneous organs, views, and devices, while supporting interpretable workflow-level analysis. Existing method…

cs.CV2026

EchoAgent: Towards Reliable Echocardiography Interpretation with "Eyes","Hands" and "Minds"

Qin Wang, Zhiqing He, Yu Liu +8

Reliable interpretation of echocardiography (Echo) is crucial for assessing cardiac function, which demands clinicians to synchronously orchestrate multiple capabilities, including…

cs.CV2026

ColoDiff: Integrating Dynamic Consistency With Content Awareness for Colonoscopy Video Generation

Junhu Fu, Shuyu Liang, Wutong Li +9

Colonoscopy video generation delivers dynamic, information-rich data critical for diagnosing intestinal diseases, particularly in data-scarce scenarios. High-quality video generati…

cs.CV2025

VAP-Diffusion: Enriching Descriptions with MLLMs for Enhanced Medical Image Generation

Peng Huang, Junhu Fu, Bowen Guo +3

As the appearance of medical images is influenced by multiple underlying factors, generative models require rich attribute information beyond labels to produce realistic and divers…