A cell-graph convolutional network grades colorectal cancer histology images by treating nuclei as graph nodes, reporting 97.0% image-level accuracy, about 1.3% above the previous best.
Global cancer statistics 2018: Globocan estimates of inci- dence and mortality worldwide for 36 cancers in 185 coun- tries
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CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images
A cell-graph convolutional network grades colorectal cancer histology images by treating nuclei as graph nodes, reporting 97.0% image-level accuracy, about 1.3% above the previous best.