Abstract:We propose a method to accurately obtain the ratio of tumor cells over an entire histological slide. We use deep fully convolutional neural network models trained to detect and classify cells on images of H&E-stained tissue sections. Pathologists' labels consisting of exhaustive nuclei locations and tumor regions were used to trained the model in a supervised fashion. We show that combining two models, each working at a different magnification allows the system to capture both cell-level details and surroundin… Show more
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