85 citations · 136 across the 33 of their papers we have counts for
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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…
RankByGene: Gene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency
Wentao Huang, Meilong Xu, Xiaoling Hu +9
Spatial transcriptomics (ST) provides essential spatial context by mapping gene expression within tissue, enabling detailed study of cellular heterogeneity and tissue organization.…
Semi-Supervised Contrastive VAE for Disentanglement of Digital Pathology Images
Mahmudul Hasan, Xiaoling Hu, Shahira Abousamra +3
Despite the strong prediction power of deep learning models, their interpretability remains an important concern. Disentanglement models increase interpretability by decomposing th…
P-Count: Persistence-based Counting of White Matter Hyperintensities in Brain MRI
Xiaoling Hu, Annabel Sorby-Adams, Frederik Barkhof +3
White matter hyperintensities (WMH) are a hallmark of cerebrovascular disease and multiple sclerosis. Automated WMH segmentation methods enable quantitative analysis via estimation…
Semi-supervised Segmentation of Histopathology Images with Noise-Aware Topological Consistency
Meilong Xu, Xiaoling Hu, Saumya Gupta +2
In digital pathology, segmenting densely distributed objects like glands and nuclei is crucial for downstream analysis. Since detailed pixel-wise annotations are very time-consumin…
Learning Probabilistic Topological Representations Using Discrete Morse Theory
Xiaoling Hu, Dimitris Samaras, Chao Chen
Accurate delineation of fine-scale structures is a very important yet challenging problem. Existing methods use topological information as an additional training loss, but are ulti…
A Topology-Attention ConvLSTM Network and Its Application to EM Images
Jiaqi Yang, Xiaoling Hu, Chao Chen +1
Structural accuracy of segmentation is important for finescale structures in biomedical images. We propose a novel TopologyAttention ConvLSTM Network (TACNet) for 3D image segmenta…