Automatic acquisition of immune cells location using deep learning for automated analysis

Abstract

In the tracking and analysis of immune cells by researchers who aim to analyze those cells, each image of immune cells is analyzed manually. If the tracking and analysis can be performed automatically using a computer, the load of researchers can be reduced and the work efficiency can be improved. Some approaches have been taken to this problem so far. However, these approaches are necessary to choose the initial location of an immune cell by hand. So we approach to extract the position of multiple immune cells to track by Deep Learning. The goal of this research is the automatic analysis of multiple immune cells on a moving image of immune cells. This paper present that evaluate methods for learning immune cell with experiment results and examine the possibility of automatic tracking.