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most citedAct Like a Pathologist: Tissue-Aware Whole Slide Image Reasoning

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cs.CV2026

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…

cs.CV20261 cited

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

LoC-Path: Learning to Compress for Pathology Multimodal Large Language Models

Qingqiao Hu, Weimin Lyu, Meilong Xu +5

Whole Slide Image (WSI) MLLMs are difficult to build and deploy because gigapixel slides induce thousands of visual tokens, while only a small fraction of regions is diagnostically…

cs.CV2026

Uncertainty Estimation for Pretrained Medical Image Registration Models via Transformation Equivariance

Lin Tian, Xiaoling Hu, Juan Eugenio Iglesias

Accurate image registration is essential in many medical imaging applications, yet most deep registration networks provide little indication of when or where their predictions are…