Automatic tracking and measurement of the motion of blood cells in microvessels based on analysis of multiple spatiotemporal images

Automatic blood cell tracking and velocity measurement in microvessels is a crucial task in biomedical and physiological research. For the analysis of the motion of blood cells in microvessels, a commonly used method for blood cell tracking and velocity estimation is spatiotemporal image-based analysis. However, in the process of the spatiotemporal image generation, a single spatial path is used, i.e. the centreline, which is not suitable for many situations in which cells do not move strictly along the central axis of the microvessel. In this paper, we propose a new method for automatic tracking and measurement of the motion of blood cells in a microvessel based on multiple spatiotemporal images analysis. First, the proposed method adopts three spatial paths (the centreline, inner and outer contour of the microvessel) to generate three spatiotemporal images; then, the traces of blood cells in the spatiotemporal images are extracted and subsequently trace grouping and fusion processes are developed for tracking cell trajectories. For extracting traces in spatiotemporal images, a steerable filter is employed to enhance the traces in raw spatiotemporal images, and then the noise suppression function and orientation-filtering function are designed to extract trace candidates. In the subsequent grouping and fusion process, trace candidates are grouped by the proposed trace grouping rule, and then the trajectories are calculated by the proposed trace fusion approach. The results validate the proposed method for blood cell tracking and the accuracy for blood cell velocity measurement. Moreover, for the larger microvessels, we discuss the criterion of the number selection of the optimal spatial path by using both simulated and real experiments, and it can be used as the criterion for blood cell tracking in microvessels