We introduce an image transform designed to highlight features with high degree of radial symmetry for identification and subpixel localization of particles in microscopy images. The transform is based on analyzing pixel value variations in radial and angular directions. We compare the subpixel localization performance of this algorithm to other common methods based on radial or mirror symmetry (such as fast radial symmetry transform, orientation alignment transform, XCorr, and quadrant interpolation), using both synthetic and experimentally obtained data. We find that in all cases it achieves the same or lower localization error, frequently reaching the theoretical limit.

Characterization of the size and material properties of particles in liquid suspensions is in very high demand, e.g., for the analysis of colloidal samples or of bodily fluids such as urine or blood plasma. However, the existing methods are limited in deciphering the constituents of realistic samples. Here, we introduce iNTA as a new method, which combines interferometric detection of scattering with nanoparticle tracking analysis, to reach an unprecedented sensitivity and precision in determining the size and refractive index distributions of nanoparticles in suspensions. After benchmarking iNTA with samples of colloidal gold, we present its remarkable ability to resolve the constituents of various multi-component and polydisperse samples of known origin. Furthermore, we showcase the method by elucidating the refractive index and size distributions of extracellular vesicles from Leishmania parasites and nanoparticles in human urine. The current performance of iNTA already enables advances in several important applications, but we also discuss possible improvements.

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