HIGHLIGHTS
- who: . and collaborators from the Tianjin University, China have published the Article: LAD-GCN: Automatic diagnostic framework for quantitative estimation of growth patterns during clinical evaluation of lung adenocarcinoma, in the Journal: (JOURNAL)
- what: The authors focus on the identification and quantification of lung adenocarcinoma tissue growth patterns from WSIs. Although CNN can automatically encode rich semantic features contained in captured images, the analysis of histopathological images often focuses on local features, which leads to biased learning. The main reason for this is that the interclass differences among tissue growth patterns are small, that is . . .
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