How do particle shape and image resolution influence accuracy of single particle tracking

Single Particle Tracking (SPT) is a crucial tool for analysing material deformation, providing sub-pixel accuracy in tracking individual particles. However, the influence of particle shape and imaging parameters on tracking accuracy remains underexplored. This study represents the first systematic examination of location errors in relation to particle shapes and sizes, and provides practical recommendations for optimizing tracking accuracy. We investigate static location errors associated with various particle shapes, including spheres, hollow spheres, and cubes. Two versions of spheres were investigated: the first scaled the grey value according to the volume occupied by the sphere, while the second version additionally scaled the grey values using a Gaussian function, depending on the distance to the particle centroid. Equivalent versions were used for cubes. Using simulated, noise-free 3D-images, we assessed the influence of particle shape, image resolution, and algorithm-specific parameters on location accuracy and the resulting strain measurement errors. Results indicate that particle shape significantly affects accuracy. Solid spheres showed the lowest mean location error — under 0.0075 voxel-size for diameters of 7 voxel-size – while hollow spheres exhibited errors up to 2.5 voxel-size. Strain error analysis revealed that a particle spacing of 50 voxel-size suffices to keep strain errors below 0.01% (suitable for engineering purposes) for spheres between 7 and 15 voxel-size in diameter. These findings provide valuable insight into improving SPT techniques in material deformation analysis, highlighting optimal particle geometries and imaging settings for accurate strain quantification. Future work should address the impact of noise and explore tracking-performance for more complex particle shapes.