  We present Bionic Tracking, a novel method for solving biological cell
tracking problems with eye tracking in virtual reality using commodity
hardware. Using gaze data, and especially smooth pursuit eye movements, we are
able to track cells in time series of 3D volumetric datasets. The problem of
tracking cells is ubiquitous in developmental biology, where large volumetric
microscopy datasets are acquired on a daily basis, often comprising hundreds or
thousands of time points that span hours or days. The image data, however, is
only a means to an end, and scientists are often interested in the
reconstruction of cell trajectories and cell lineage trees. Reliably tracking
cells in crowded three-dimensional space over many timepoints remains an open
problem, and many current approaches rely on tedious manual annotation and
curation. In our Bionic Tracking approach, we substitute the usual 2D
point-and-click annotation to track cells with eye tracking in a virtual
reality headset, where users simply have to follow a cell with their eyes in 3D
space in order to track it. We detail the interaction design of our approach
and explain the graph-based algorithm used to connect different time points,
also taking occlusion and user distraction into account. We demonstrate our
cell tracking method using the example of two different biological datasets.
Finally, we report on a user study with seven cell tracking experts,
demonstrating the benefits of our approach over manual point-and-click
tracking.
