Automated nucleus detection with deep learning

Examining the response of a cell to a certain treatment, disease, or phenomenon is the initial step for most biological analyses. Since the human body contains over 30 trillion cells and most of them contain nuclei with DNA, being able to rapidly and precisely localize the nuclei is crucial for a researcher to understand the biological processes. In this post we present a possible approach for automated nucleus detection. The algorithm is based on Mask R-CNN, a state-of-the-art deep learning method for object detection and detailed segmentation.