1 citations · 1 across the 2 of their papers we have counts for
5 papers
PathFLIP: Fine-grained Language-Image Pretraining for Versatile Computational Pathology
Fengchun Liu, Songhan Jiang, Linghan Cai +2
While Vision-Language Models (VLMs) have achieved notable progress in computational pathology (CPath), the gigapixel scale and spatial heterogeneity of Whole Slide Images (WSIs) co…
PathReasoner-R1: Instilling Structured Reasoning into Pathology Vision-Language Model via Knowledge-Guided Policy Optimization
Songhan Jiang, Fengchun Liu, Ziyue Wang +2
Vision-Language Models (VLMs) are advancing computational pathology with superior visual understanding capabilities. However, current systems often reduce diagnosis to directly out…
The Four Color Theorem for Cell Instance Segmentation
Ye Zhang, Yu Zhou, Yifeng Wang +4
Cell instance segmentation is critical to analyzing biomedical images, yet accurately distinguishing tightly touching cells remains a persistent challenge. Existing instance segmen…
DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation via Cross-Task Interactions
Ye Zhang, Yifeng Wang, Zijie Fang +4
Weakly supervised segmentation methods have gained significant attention due to their ability to reduce the reliance on costly pixel-level annotations during model training. Howeve…
Dynamic Pseudo Label Optimization in Point-Supervised Nuclei Segmentation
Ziyue Wang, Ye Zhang, Yifeng Wang +2
Deep learning has achieved impressive results in nuclei segmentation, but the massive requirement for pixel-wise labels remains a significant challenge. To alleviate the annotation…