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20242026
most citedU-KAN Makes Strong Backbone for Medical Image Segmentation and Generation

47 citations · 60 across the 10 of their papers we have counts for

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5 papers · 1 filter

eess.IV2024★ 1 cited

DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation

Xinyu Liu, Wuyang Li, Yixuan Yuan

Semi-supervised medical image segmentation aims to leverage limited annotated data and rich unlabeled data to perform accurate segmentation. However, existing semi-supervised metho…

cs.CV2024★ 2 cited

GTP-4o: Modality-prompted Heterogeneous Graph Learning for Omni-modal Biomedical Representation

Chenxin Li, Xinyu Liu, Cheng Wang +4

Recent advances in learning multi-modal representation have witnessed the success in biomedical domains. While established techniques enable handling multi-modal information, the c…

eess.IV2024★ 47 cited

U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation

Chenxin Li, Xinyu Liu, Wuyang Li +5

U-Net has become a cornerstone in various visual applications such as image segmentation and diffusion probability models. While numerous innovative designs and improvements have b…

cs.CV2024★ 1 cited

Endora: Video Generation Models as Endoscopy Simulators

Chenxin Li, Hengyu Liu, Yifan Liu +6

Generative models hold promise for revolutionizing medical education, robot-assisted surgery, and data augmentation for machine learning. Despite progress in generating 2D medical…

eess.IV2024★ 9 cited

UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images

Zhen Chen, Qing Xu, Xinyu Liu +1

In digital pathology, precise nuclei segmentation is pivotal yet challenged by the diversity of tissue types, staining protocols, and imaging conditions. Recently, the segment anyt…