9 citations · 22 across the 13 of their papers we have counts for
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eess.IV2024★ 9 cited
NuSegDG: Integration of Heterogeneous Space and Gaussian Kernel for Domain-Generalized Nuclei Segmentation
Zhenye Lou, Qing Xu, Zekun Jiang +6
Domain-generalized nuclei segmentation refers to the generalizability of models to unseen domains based on knowledge learned from source domains and is challenged by various image…
eess.IV2024★ 3 cited
De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
Qing Xu, Jiaxuan Li, Xiangjian He +8
The universality of deep neural networks across different modalities and their generalization capabilities to unseen domains play an essential role in medical image segmentation. T…
eess.IV2024★ 9 cited
UN-SAM: Universal Prompt-Free Segmentation for Generalized Nuclei Images
Zhen Chen, Qing Xu, Xinyu Liu +1
In digital pathology, precise nuclei segmentation is pivotal yet challenged by the diversity of tissue types, staining protocols, and imaging conditions. Recently, the segment anyt…