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Cancer Detection In Radical Prostatectomy Histology Using Convolutional Neural Networks, Laurie Huang
Cancer Detection In Radical Prostatectomy Histology Using Convolutional Neural Networks, Laurie Huang
Electronic Thesis and Dissertation Repository
Radical prostatectomy (RP) is a common treatment for prostate cancer. We used RP whole-mount tissue samples from 68 patients stained with haematoxylin and eosin to create cancer maps using four pretrained networks: AlexNet, NASNet, VGG16 and Xception, to classify regions of interest (ROIs) as cancer or non-cancer. Models were trained on either raw images or as tissue component maps (TCMs) containing nuclei, lumina and stroma/other components generated from a trained U-Net.
All models performed similarly; however, VGG16 trained on raw images performed with the highest area under the receiver operating characteristic curve (AUC) of 0.994 (95% confidence interval 0.992-0.996). Ensemble …