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Fig. 1 | Breast Cancer Research

Fig. 1

From: Quantitative nuclear histomorphometric features are predictive of Oncotype DX risk categories in ductal carcinoma in situ: preliminary findings

Fig. 1

Illustration of the overall workflow: (1) Regions of DCIS were annotated on the whole slide image (WSI) by an experienced breast pathologist. (2) Nuclei were segmented from the annotated tumor region via a deep learning model [16]. (3) Nuclear histomorphometric features were extracted. (4) The features were then evaluated in their ability to distinguish different ODx risk categories via supervised classification and unsupervised clustering approaches

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