A Cytology Support System for Urothelial Cells That Provides Diagnostic Evidence

Abstract

In order to develop a cytology support system, we first apply U-Net to separate the cytoplasm region, nucleus region, and background. After that, we extract 28 features from cell regions and a malignant judgement level was predicted by regression analysis. As a result, for isolated urothelial cells, we were able to identify malignant cells with high accuracy (area under the curve (AUC): 0.914). We also developed a system that quantitatively presents the degree of atypia, which is the basis for diagnosis, by classifying the calculated atypia into five groups according to the characteristics of malignant cells and performing statistical processing.