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20242026
most citedAn Active Learning Pipeline for Biomedical Image Instance Segmentation with Minimal Human Intervention

3 citations · 3 across the 8 of their papers we have counts for

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cs.CV20253 cited

An Active Learning Pipeline for Biomedical Image Instance Segmentation with Minimal Human Intervention

Shuo Zhao, Yu Zhou, Jianxu Chen

Biomedical image segmentation is critical for precise structure delineation and downstream analysis. Traditional methods often struggle with noisy data, while deep learning models…

cs.CV2025

Data Efficiency and Transfer Robustness in Biomedical Image Segmentation: A Study of Redundancy and Forgetting with Cellpose

Shuo Zhao, Jianxu Chen

Generalist biomedical image segmentation models such as Cellpose are increasingly applied across diverse imaging modalities and cell types. However, two critical challenges remain…

cs.CV2025

Cell Instance Segmentation: The Devil Is in the Boundaries

Peixian Liang, Yifan Ding, Yizhe Zhang +9

State-of-the-art (SOTA) methods for cell instance segmentation are based on deep learning (DL) semantic segmentation approaches, focusing on distinguishing foreground pixels from b…

cs.CV2025

PathMR: Multimodal Visual Reasoning for Interpretable Pathology Diagnosis

Ye Zhang, Yu Zhou, Jingwen Qi +11

Deep learning based automated pathological diagnosis has markedly improved diagnostic efficiency and reduced variability between observers, yet its clinical adoption remains limite…

cs.CV2025

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…