1 citations · 1 across the 4 of their papers we have counts for
4 papers
Weakly Supervised Contrastive Learning for Histopathology Patch Embeddings
Bodong Zhang, Xiwen Li, Hamid Manoochehri +4
Digital histopathology whole slide images (WSIs) provide gigapixel-scale high-resolution images that are highly useful for disease diagnosis. However, digital histopathology image…
CLASS-M: Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification
Bodong Zhang, Hamid Manoochehri, Man Minh Ho +5
Histopathological image classification is an important task in medical image analysis. Recent approaches generally rely on weakly supervised learning due to the ease of acquiring c…
A Pathologist-Informed Workflow for Classification of Prostate Glands in Histopathology
Alessandro Ferrero, Beatrice Knudsen, Deepika Sirohi +1
Pathologists diagnose and grade prostate cancer by examining tissue from needle biopsies on glass slides. The cancer's severity and risk of metastasis are determined by the Gleason…
Stain Based Contrastive Co-training for Histopathological Image Analysis
Bodong Zhang, Beatrice Knudsen, Deepika Sirohi +2
We propose a novel semi-supervised learning approach for classification of histopathology images. We employ strong supervision with patch-level annotations combined with a novel co…