Figure 1.

Overall workflow showing the steps to analyze the correlation of the automated mitotic count with ODX and to use mitotic Information In BCa risk stratification. In the training stage, HPFs from several WSI are extracted and a nuclei detection method is applied on each HPF. Each of the candidate nuclei is classied as mitotic or not using a DNN classifier. Subsequently, the mitotic information is used to train a linear support vector machine classifier. During testing, the nuclei identification algorithm and the DNN classifier are used again in the cancerous regions of the WSI. Finally, the resulting mitotic information is used by the support vector machine classifier to predict the WSI risk either as high or low. [Color figure can be viewed at wileyonlinelibrary.com]