117 citations · 135 across the 7 of their papers we have counts for
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q-bio.QM2021★ 2 cited
A Histopathology Study Comparing Contrastive Semi-Supervised and Fully Supervised Learning
Lantian Zhang, Mohamed Amgad, Lee A. D. Cooper
Data labeling is often the most challenging task when developing computational pathology models. Pathologist participation is necessary to generate accurate labels, and the limitat…
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…