117 citations · 128 across the 2 of their papers we have counts for
2 papers
eess.IV2021★ 117 cited
NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation
Mohamed Amgad, Lamees A. Atteya, Hagar Hussein +34
High-resolution mapping of cells and tissue structures provides a foundation for developing interpretable machine-learning models for computational pathology. Deep learning algorit…
q-bio.QM2020★ 11 cited
HistomicsML2.0: Fast interactive machine learning for whole slide imaging data
Sanghoon Lee, Mohamed Amgad, Deepak R. Chittajallu +6
Extracting quantitative phenotypic information from whole-slide images presents significant challenges for investigators who are not experienced in developing image analysis algori…