1 citations · 1 across the 8 of their papers we have counts for
5 papers · 1 filter
NuNext: Reframing Nucleus Detection as Next-Point Detection
Zhongyi Shui, Honglin Li, Xiaozhong Ji +7
Nucleus detection in histopathology is pivotal for a wide range of clinical applications. Existing approaches either regress nuclear proxy maps that require complex post-processing…
DeNuC: Decoupling Nuclei Detection and Classification in Histopathology
Zijiang Yang, Chen Kuang, Dongmei Fu
Pathology Foundation Models (FMs) have shown strong performance across a wide range of pathology image representation and diagnostic tasks. However, FMs do not exhibit the expected…
MUSE: Multi-Scale Dense Self-Distillation for Nucleus Detection and Classification
Zijiang Yang, Hanqing Chao, Bokai Zhao +10
Nucleus detection and classification (NDC) in histopathology analysis is a fundamental task that underpins a wide range of high-level pathology applications. However, existing meth…
From Histopathology Images to Cell Clouds: Learning Slide Representations with Hierarchical Cell Transformer
Zijiang Yang, Zhongwei Qiu, Tiancheng Lin +13
It is clinically crucial and potentially very beneficial to be able to analyze and model directly the spatial distributions of cells in histopathology whole slide images (WSI). How…
From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba
Zhongwei Qiu, Hanqing Chao, Tiancheng Lin +12
Histopathology plays a critical role in medical diagnostics, with whole slide images (WSIs) offering valuable insights that directly influence clinical decision-making. However, th…