  Confocal microscopy in combination with real-space particle tracking has
proven to be a powerful tool in scientific fields such as soft matter physics,
materials science and cell biology. However, 3D tracking of anisotropic
particles in concentrated phases remains not as optimized compared to
algorithms for spherical particles. To address this problem, we developed a new
particle-fitting algorithm that can extract the positions and orientations of
fluorescent rod-like particles from three dimensional confocal microscopy data
stacks, even when the fluorescent signals of the particles overlap
considerably. We demonstrate that our algorithm correctly identifies all five
coordinates of uniaxial particles in both a concentrated disordered phase and a
liquid-crystalline smectic-B phase. Apart from confocal microscopy images, we
also demonstrate that the algorithm can be used to identify nanorods in 3D
electron tomography reconstructions. Lastly, we determined the accuracy of the
algorithm using both simulated and experimental confocal microscopy data-stacks
of diffusing silica rods in a dilute suspension. This novel particle-fitting
algorithm allows for the study of structure and dynamics in both dilute and
dense liquid-crystalline phases (such as nematic, smectic and crystalline
phases) as well as the study of the glass transition of rod-like particles in
three dimensions on the single particle level.
