9 papers
CellPath-Bench: A Multidimensional Benchmark for Whole-Slide Cellular Representations in Pathology Foundation Models
Bokai Zhao, Yiyang Zhang, Hanqing Chao +6
Pathology foundation models (PFMs) are increasingly used as general-purpose backbones, yet existing benchmarks cannot systematically diagnose their whole-slide cellular representat…
DaX: Learning General Pathology Representations Across Scales
Bokai Zhao, Yiyang Zhang, Long Bai +3
Computational pathology requires visual representations that transfer across diverse clinical endpoints and remain robust to variation in magnification, staining, scanner type, sli…
Benchmarking Pathology Foundation Models for Spatial Domain Understanding
Bokai Zhao, Yiyang Zhang, Yuanchi Zhu +6
Pathology foundation models (PFMs) have emerged as a core approach for learning transferable representations from whole slide images (WSIs), and they are typically benchmarked thro…
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…
Neural Proteomics Fields for Super-resolved Spatial Proteomics Prediction
Bokai Zhao, Weiyang Shi, Hanqing Chao +4
Spatial proteomics maps protein distributions in tissues, providing transformative insights for life sciences. However, current sequencing-based technologies suffer from low spatia…
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…