116 citations · 119 across the 5 of their papers we have counts for
5 papers
StainPresetNet: Stain Preset Network for Fast Multi-to-Multi Stain Normalization
Hongtao Kang, Die Luo, Li Chen +4
Stain normalization reduces color variations caused by variations in staining protocols and imaging conditions, thereby enhancing computer-aided diagnostic system performance. Trad…
From Generic to Specialized: A Subspecialty Diagnostic System Powered by Self-Supervised Learning for Cervical Histopathology
Yizhi Wang, Li Chen, Qiang Huang +24
Cervical cancer remains a major malignancy, necessitating extensive and complex histopathological assessments and comprehensive support tools. Although deep learning shows promise,…
ParamNet: A Dynamic Parameter Network for Fast Multi-to-One Stain Normalization
Hongtao Kang, Die Luo, Li Chen +5
In practice, digital pathology images are often affected by various factors, resulting in very large differences in color and brightness. Stain normalization can effectively reduce…
An Efficient Cervical Whole Slide Image Analysis Framework Based on Multi-scale Semantic and Location Deep Features
Ziquan Wei, Shenghua Cheng, Junbo Hu +3
Digital gigapixel whole slide image (WSI) is widely used in clinical diagnosis, and automated WSI analysis is key for computer-aided diagnosis. Currently, analyzing the integrated…
StainNet: a fast and robust stain normalization network
Hongtao Kang, Die Luo, Weihua Feng +4
Stain normalization often refers to transferring the color distribution of the source image to that of the target image and has been widely used in biomedical image analysis. The c…