1 citations · 2 across the 9 of their papers we have counts for
10 papers
Topo-R1: Detecting Topological Anomalies via Vision-Language Models
Meilong Xu, Qingqiao Hu, Xiaoling Hu +6
Topology is critical in tubular structures such as blood vessels, nerve fibers, and road networks, where connectivity and loop structure govern downstream functional analysis. Visi…
Act Like a Pathologist: Tissue-Aware Whole Slide Image Reasoning
Wentao Huang, Weimin Lyu, Peiliang Lou +8
Computational pathology has advanced rapidly in recent years, driven by domain-specific image encoders and growing interest in using vision-language models to answer natural-langua…
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…
Adversarial Vessel-Unveiling Semi-Supervised Segmentation for Retinopathy of Prematurity Diagnosis
Gozde Merve Demirci, Jiachen Yao, Ming-Chih Ho +4
Accurate segmentation of retinal images plays a crucial role in aiding ophthalmologists in diagnosing retinopathy of prematurity (ROP) and assessing its severity. However, due to t…
Text-Driven Weakly Supervised OCT Lesion Segmentation with Structural Guidance
Jiaqi Yang, Nitish Mehta, Xiaoling Hu +2
Accurate segmentation of Optical Coherence Tomography (OCT) images is crucial for diagnosing and monitoring retinal diseases. However, the labor-intensive nature of pixel-level ann…
Hard Negative Sample Mining for Whole Slide Image Classification
Wentao Huang, Xiaoling Hu, Shahira Abousamra +2
Weakly supervised whole slide image (WSI) classification is challenging due to the lack of patch-level labels and high computational costs. State-of-the-art methods use self-superv…
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…
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…
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…