A New Approach for Cell Detection and Tracking

Abstract

In recent years, cell tracking methods by detection have become more and more popular because they outperformed cell tracking methods by contour evolution in most practical cell tracking applications. Yet, the most frequently used segmentation technique by cell detection methods is still threshold selection that is determined manually or by algorithms proposed in the 1970s. As a whole, these old threshold selection methods could not meet the accuracy requirement of cell detection adequately. In this paper, we propose a new approach of cell tracking by detection based on a multiple-threshold segmentation method that calculates multiple thresholds automatically and robustly. After cell detection, the proposed approach generates the timeline moving trajectory of a cell by connecting the cell positions along the time lapse image sequences based on morphological operations. We use four types of cells to verify the effectiveness of the proposed approach and the experimental results are favorable.

Keywords

• Threshold selection
• image segmentation
• cell segmentation
• cell detection
• cell tracking