Detection of Cell Nuclei using LadderNet

Cytology which directly examines cells in the early detection of cancer plays an important role but this diagnosis depends on the experience and technology of a pathologist. The problem is that it takes time and the objectivity is poor. An automatic diagnosis system for pathologically diagnosing cancer is necessary to solve these problems. To classify cells into benign or malignant automatically, it is important to detect the cell nucleus from the cell image in advance. This paper proposes a new approach to detect cell nuclei for automatically using LadderNet which is a recent extension model of U-Net used in the Deep Learning Approach.