3 papers
cs.CV2025
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…
cs.CV2025
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels
Erjian Guo, Zicheng Wang, Zhen Zhao +1
Accurate medical image segmentation is often hindered by noisy labels in training data, due to the challenges of annotating medical images. Prior research works addressing noisy la…
eess.IV2024
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…