4 citations · 5 across the 4 of their papers we have counts for
3 papers
cs.CV2022★ 4 cited
Unsupervised Dense Nuclei Detection and Segmentation with Prior Self-activation Map For Histology Images
Pingyi Chen, Chenglu Zhu, Zhongyi Shui +4
The success of supervised deep learning models in medical image segmentation relies on detailed annotations. However, labor-intensive manual labeling is costly and inefficient, esp…
eess.IV2022
Weakly Supervised Learning for cell recognition in immunohistochemical cytoplasm staining images
Shichuan Zhang, Chenglu Zhu, Honglin Li +2
Cell classification and counting in immunohistochemical cytoplasm staining images play a pivotal role in cancer diagnosis. Weakly supervised learning is a potential method to deal…
cs.CV2021★ 1 cited
Generalizing Nucleus Recognition Model in Multi-source Images via Pruning
Jiatong Cai, Chenglu Zhu, Can Cui +4
Ki67 is a significant biomarker in the diagnosis and prognosis of cancer, whose index can be evaluated by quantifying its expression in Ki67 immunohistochemistry (IHC) stained imag…