Toward Simple & Scalable 3D Cell Tracking

Toxoplasma gondii is an obligate intracellular parasitic that is the causative agent of disseminated toxoplasmosis. Roughly, one third of the worlds population will test positive for T. gondii. Its virulence is linked to its lytic cycle and is predicated on its motility and ability to enter and exit nucleated cells; therefore, studies elucidating its mechanism of motility and in particular, its motility patterns in the context of its lytic cycle, are critical to the eventual development of therapeutic strategies. Here, we present an end-to-end computational pipeline for detection and tracking of T. gondii cells in 3D videos. Our pipeline consists of four different modules including: Preprocessing, Sparsification, Cell Detection, and Cell Tracking. By identifying key bottlenecks in object tracking and leveraging domain-specific heuristics, we developed a lightweight and highly parallel tracking procedure. Our results indicate that the parallel version of our pipeline performs remarkably faster than the serial one, and lays the groundwork for a novel, large-scale tracking algorithm.