1 citations · 1 across the 3 of their papers we have counts for
6 papers
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…
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…
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…
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…
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…