162 citations · 186 across the 12 of their papers we have counts for
5 papers · 1 filter
DeepNoise: Signal and Noise Disentanglement based on Classifying Fluorescent Microscopy Images via Deep Learning
Sen Yang, Tao Shen, Yuqi Fang +5
The high-content image-based assay is commonly leveraged for identifying the phenotypic impact of genetic perturbations in biology field. However, a persistent issue remains unsolv…
Mitosis domain generalization in histopathology images -- The MIDOG challenge
Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram +32
The density of mitotic figures within tumor tissue is known to be highly correlated with tumor proliferation and thus is an important marker in tumor grading. Recognition of mitoti…
Deep learning-based approach to reveal tumor mutational burden status from whole slide images across multiple cancer types
Siteng Chen, Jinxi Xiang, Xiyue Wang +6
Tumor mutational burden (TMB) is a potential genomic biomarker of immunotherapy. However, TMB detected through whole exome sequencing lacks clinical penetration in low-resource set…
A Deep Learning Framework for Nuclear Segmentation and Classification in Histopathological Images
Sen Yang, Jinxi Xiang, Xiyue Wang
Nucleus segmentation and classification are the prerequisites in the workflow of digital pathology processing. However, it is very challenging due to its high-level heterogeneity a…
Keep It Accurate and Robust: An Enhanced Nuclei Analysis Framework
Wenhua Zhang, Sen Yang, Meiwei Luo +5
Accurate segmentation and classification of nuclei in histology images is critical but challenging due to nuclei heterogeneity, staining variations, and tissue complexity. Existing…