Supporting information for a novel acausal method for tracking microswimmers in 3D

Quantitative tracking of rapidly swimming micron-scale objects remains an elusive challenge in digital holographic microscopy (DHM) due to low signal-to-noise. The paper describes a novel method for tracking micron-sized motile organisms in off-axis DHM raw holograms and/or reconstructions. We begin by processing the microscopic images with the previously reported Holographic Examination for Life-like Motility (HELM) software, which provides a variety of tracking outputs including motion history images (MHIs). MHIs are stills of videos where the positions of objects are indicated with color time-coding. The visible tracks in the MHIs are superior to tracks identified by all tested automated tracking algorithms, particularly in low signal-to-noise ratio data, but do not provide quantitative track data. Here we use these tracks, rather than object identification in individual frames, as a basis for quantitative tracking of Bacillus subtilis by first generating MHIs from X,Y, t stacks (raw holograms or a projection over reconstructed planes), then using a region-tracking algorithm to identify and separate swimming pathways. Subsequently, we identify the object’s Z plane of best focus at the corresponding X, Y, and t points, yielding a full description of the swimming pathways in three spatial dimensions plus time. This approach offers an alternative to object-based tracking for processing large, low signal-to-noise datasets containing highly motile organisms.