10 papers
CARD: Calibration via Agreement in Reverse Diffusion for Out-of-Domain MRI Segmentation
Jiaheng Dai, Weidong Guo, Qingbiao Li +4
Probability calibration aligns model confidence with predictive accuracy, enabling clinicians to identify unreliable segmentation regions. This alignment breaks down under domain s…
CIPHER: Causal Intervention Pathways for Healthcare Equity and Robustness
Xinyu Jia, Weidong Guo, Wangyuan Zhao +3
Deep learning models for medical diagnosis frequently exhibit substantial performance disparities across sensitive subgroups (e.g., race, sex), even when average accuracy is high.…
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…
Defining Robust Ultrasound Quality Metrics via an Ultrasound Foundation Model
Ziyang Huang, Bingyan Li, Chen Ma +6
Clinicians lack a principled framework to quantify diagnostic utility in ultrasound reconstructions. Existing standards like PSNR and VGG-LPIPS are inadequate, failing to account f…
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…
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…
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…
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…
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…
SAM-MPA: Applying SAM to Few-shot Medical Image Segmentation using Mask Propagation and Auto-prompting
Jie Xu, Xiaokang Li, Chengyu Yue +2
Medical image segmentation often faces the challenge of prohibitively expensive annotation costs. While few-shot learning offers a promising solution to alleviate this burden, conv…