2 citations · 2 across the 4 of their papers we have counts for
5 papers
MATCH: Multi-faceted Adaptive Topo-Consistency for Semi-Supervised Histopathology Segmentation
Meilong Xu, Xiaoling Hu, Shahira Abousamra +2
In semi-supervised segmentation, capturing meaningful semantic structures from unlabeled data is essential. This is particularly challenging in histopathology image analysis, where…
Multi-Channel Uncertainty-Weighted Score Matching for Conditional Diffusion in Medical UDA
Chen Li, Meilong Xu, Xiaoling Hu +2
Robust medical image segmentation across modalities remains challenging due to severe domain shifts and the lack of target-domain labels. While diffusion models have been explored…
TopoCellGen: Generating Histopathology Cell Topology with a Diffusion Model
Meilong Xu, Saumya Gupta, Xiaoling Hu +5
Accurately modeling multi-class cell topology is crucial in digital pathology, as it provides critical insights into tissue structure and pathology. The synthetic generation of cel…
Spatial Diffusion for Cell Layout Generation
Chen Li, Xiaoling Hu, Shahira Abousamra +2
Generative models, such as GANs and diffusion models, have been used to augment training sets and boost performances in different tasks. We focus on generative models for cell dete…
Calibrating Uncertainty for Semi-Supervised Crowd Counting
Chen Li, Xiaoling Hu, Shahira Abousamra +1
Semi-supervised crowd counting is an important yet challenging task. A popular approach is to iteratively generate pseudo-labels for unlabeled data and add them to the training set…