A Feature Weighted Tracking Method for 3D Neutrophils in Time-lapse Microscopy

Neutrophils are one of the Neutrophils are one of the crucial immune cells. It plays a key role in the immune system defending the invasion of harmful particles, such as viruses and bacteria. The analysis of the dynamic process of neutrophil migration helps biologists to understand underlying mechanisms of neutrophils in response to wounding. However, accurate neutrophil tracking is still a challenging task in 3D space due to the complexity of cell morphology and behavior. In this study, we improved the quality of raw data by denoising and linear interpolation. A 3D U-Net was trained and used to detect the location of each cell in the time-lapse movie. Subsequently, a feature weighted 3D tracking method was proposed. The experimental results show that our method performs well compared to the existing tracking algorithm. Our pipeline is also much more reproducible than other state-of-arts.