3 citations · 5 across the 5 of their papers we have counts for
5 papers
Surg-UniWorld: A Unified Surgical World Model with Multimodal Control Experts
Rulin Zhou, Wanhao Liu, Guoheng Ma +8
Controllable surgical world models can provide a generative foundation for surgical artificial intelligence and simulation by synthesizing realistic instrument--tissue interactions…
EndoIR: Degradation-Agnostic All-in-One Endoscopic Image Restoration via Noise-Aware Routing Diffusion
Tong Chen, Xinyu Ma, Long Bai +3
Endoscopic images often suffer from diverse and co-occurring degradations such as low lighting, smoke, and bleeding, which obscure critical clinical details. Existing restoration m…
DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labels
Erjian Guo, Zhen Zhao, Zicheng Wang +3
Medical Visual Question Answering (Med-VQA) systems benefit the interpretation of medical images containing critical clinical information. However, the challenge of noisy labels an…
SurgSora: Object-Aware Diffusion Model for Controllable Surgical Video Generation
Tong Chen, Shuya Yang, Junyi Wang +3
Surgical video generation can enhance medical education and research, but existing methods lack fine-grained motion control and realism. We introduce SurgSora, a framework that gen…
LighTDiff: Surgical Endoscopic Image Low-Light Enhancement with T-Diffusion
Tong Chen, Qingcheng Lyu, Long Bai +5
Advances in endoscopy use in surgeries face challenges like inadequate lighting. Deep learning, notably the Denoising Diffusion Probabilistic Model (DDPM), holds promise for low-li…