A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization.
Ruichen Rong et al., Mod Pathol, 2024
Deep learning of cell spatial organizations identifies clinically relevant insights in tissue images.
Shidan Wang et al., Nature Communications, 2023
Unsupervised domain adaptation for nuclei segmentation: Adapting from hematoxylin & eosin stained slides to immunohistochemistry stained slides using a curriculum approach.
Shidan Wang et al.,Computer Methods and Programs in Biomedicine, 2023
Deep learning-based H-score quantification of immunohistochemistry-stained images.
Zhuoyu Wen et al.,Modern Pathology. , 2023
A Deep Learning Approach for Histology-Based Nucleus Segmentation and Tumor Microenvironment Characterization.
Ruichen Rong et al.,Nature Machine Intelligence, 2023
Image-based quantification of histological features as a function of spatial location using the Tissue Positioning System.
Ruichen Rong et al., EBioMedicine., 2023
Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images.
Zhuoyu Wen. et al., Genes, 2023