4 citations · 9 across the 11 of their papers we have counts for
11 papers
Large-scale cervical precancerous screening via AI-assisted cytology whole slide image analysis
Honglin Li, Yusuan Sun, Chenglu Zhu +8
Cervical Cancer continues to be the leading gynecological malignancy, posing a persistent threat to women's health on a global scale. Early screening via cytology Whole Slide Image…
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels
Zixia Jia, Junpeng Li, Shichuan Zhang +2
Traditional supervised learning heavily relies on human-annotated datasets, especially in data-hungry neural approaches. However, various tasks, especially multi-label tasks like d…
Multi-modal Learning with Missing Modality in Predicting Axillary Lymph Node Metastasis
Shichuan Zhang, Sunyi Zheng, Zhongyi Shui +2
Multi-modal Learning has attracted widespread attention in medical image analysis. Using multi-modal data, whole slide images (WSIs) and clinical information, can improve the perfo…
Exploring Unsupervised Cell Recognition with Prior Self-activation Maps
Pingyi Chen, Chenglu Zhu, Zhongyi Shui +4
The success of supervised deep learning models on cell recognition tasks relies on detailed annotations. Many previous works have managed to reduce the dependency on labels. Howeve…
Masked conditional variational autoencoders for chromosome straightening
Jingxiong Li, Sunyi Zheng, Zhongyi Shui +9
Karyotyping is of importance for detecting chromosomal aberrations in human disease. However, chromosomes easily appear curved in microscopic images, which prevents cytogeneticists…
Semi-supervised Cell Recognition under Point Supervision
Zhongyi Shui, Yizhi Zhao, Sunyi Zheng +6
Cell recognition is a fundamental task in digital histopathology image analysis. Point-based cell recognition (PCR) methods normally require a vast number of annotations, which is…
DPA-P2PNet: Deformable Proposal-aware P2PNet for Accurate Point-based Cell Detection
Zhongyi Shui, Sunyi Zheng, Chenglu Zhu +6
Point-based cell detection (PCD), which pursues high-performance cell sensing under low-cost data annotation, has garnered increased attention in computational pathology community.…
CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image Segmentation
Ran Gu, Guotai Wang, Jiangshan Lu +8
Generalization to previously unseen images with potential domain shifts and different styles is essential for clinically applicable medical image segmentation, and the ability to d…
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…
End-to-end cell recognition by point annotation
Zhongyi Shui, Shichuan Zhang, Chenglu Zhu +4
Reliable quantitative analysis of immunohistochemical staining images requires accurate and robust cell detection and classification. Recent weakly-supervised methods usually estim…
HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy
Hao Fu, Guotai Wang, Wenhui Lei +5
Accurate segmentation of Anatomical brain Barriers to Cancer spread (ABCs) plays an important role for automatic delineation of Clinical Target Volume (CTV) of brain tumors in radi…