Fig. 1. Schematic of image-based single-particle tracking

Fig. 2. Overview of 3D tracking methods via closed-loop feedback control covered in this review

Fig. 3. Tetrahedral detection-based 3D tracking. (a) Schematic of the tetrahedral detection-based 3D tracking system developed by Han et al.^[58], in which two pairs of optical fibers form a three-dimensional tetrahedral detection region within the sample space; (b) three-dimensional trajectory of five quantum dot-labeled IgE-FcεRI complexes, with trajectory points color-coded according to time; (c) photon count data used for closed-loop feedback control and tracking; (d) representative camera image acquired near the starting point; (e) MSD analysis of directional motion^[57]; (f) single-molecule tracking analysis of Azami Green oligomers (mAG, dAG, and tAG) in glycerol solution^[58], considering only trajectories with tracking durations ≥100 ms

Fig. 4. Split-detection 3D tracking. (a) Schematics of the system^[63]; (b) snapshot from tracking video at 30 frame/s; (c) long-term 3D tracking of 80 nm particles with trajectory points color-coded by time^[62]

Fig. 5. Tetrahedral excitation 3D tracking. (a) Schematic of TSUNAMI; (b) verification of the time interval of the four lasers by measuring the fluorescent signal at the center of the detection volume; (c) schematic of the tetrahedral PSF; (d) scanned images of 100 nm fluorescent microspheres at different depths

Fig. 6. Principle of orbital tracking, the laser (blue) scans around the particle (green) in a circular pattern. (a) When the particle is located at the center of the orbital scan, its fluorescence intensity remains stable over time; (b) when the particle deviates from the center, its fluorescence intensity varies sinusoidally; (c) two focal planes are scanned axially in sequence, and the particle's axial position is calculated from the signal difference between them

Fig. 7. Laser-scanning-based orbital tracking^[73]. (a) Schematic of 3D orbital tracking using ETL; (b) comparison of the response times of the piezoelectric stage and ETL during an 8.192 ms orbital scanning cycle, showing that the ETL provides a faster response

Fig. 8. Orbital scanning 3D single particle tracking with bi-plane detection. (a) Schematic of biplane simultaneous monitoring using two SPC-APDs^[76]; (b) high-speed laser scanning via 2 acousto-optic modulators^[79]

Fig. 9. 3D-DyPLoT.(a) Schematics of the system^[88]; (b) 3D tracking trajectory of single DFHBI-1T-labeled mRNA in glycerol^[89]

Fig. 10. MINFLUX. (a) Schematic of MINFLUX^[95]; (b) laser scanning and photon collection; (c) relationship between localization precision and temporal resolution; (d) schematic of p-MINFLUX system^[100]

Fig. 11. Schematic of 3D single-particle tracking via extremum seeking^[101]

Fig. 12. 3D single-molecule tracking via cross-entropy minimization^[102]. (a) Schematic of the system; (b) spatial distribution array of the laser focus generated by the EOD; (c) schematic representation of real-time feedback tracking and data post-processing

Fig. 13. Single-particle tracking with asynchronous read-out SPAD array^[103]. (a) Schematic of the system; (b) when the particle exhibits 2D movement relative to the field-of-view center, the micro-image spot shifts and the I_m value decreases, combined with fluorescence lifetime τ analysis, this triggers the galvanometric mirror repositioning mechanism; (c) fluorescence lifetime is extracted from the delay histogram Δt_em between the excitation pulse time t_exc and the photon detection time t_d; (d) astigmatism is introduced using a cylindrical lens, enabling axial position determination based on symmetry changes in the particle's micro-image

Fig. 14. Image-based 3D tracking. (a) Schematic of the three-dimensional tracking system based on bi-plane imaging^[104]; (b)schematic of the three-dimensional tracking system based on light-sheet illumination^[105]; (c) schematic of the three-dimensional tracking system based on bi-plane parallax imaging and deep learning-assisted automated^[106]

Fig. 15. Photoactivated mitochondrial tracking in axons^[108]. (a) Wide-field image reveals the anterograde transport of a photo-activated mitochondrion along a single axon; (b) mean photon count rate of both detection channels; (c) 3D trajectory of the moving mitochondrion

Fig. 16. Three-dimensional tracking analysis of SWNTs in HeLa cells^[76]. (a) Overlaid 2D location of 18 SWNT trajectories in relation to HeLa cell (yellow outline); (b) master plot of the translational, rotational diffusion coefficients, types of diffusion, and corral volumes or active transport velocities for 18 measured trajectories; (c) 3D trajectories and corresponding MSD curves of three typical diffusion modes: normal diffusion, convective diffusion, and corralled diffusion; (d) 3D trajectory maps color-coded by fluorescence intensity, reflecting signal fluctuations during tracking; (e) aggregation behavior of SWNTs after 1.5 h incubation

Fig. 17. Three-dimensional dynamic tracking of single viral particles. (a) 3D-PART tracking of single virus-like particles (VLPs) on HuH7 cell membranes^[88]; (b) top-down view of single VLP tracking; (c) magnified view of single VLP tracking, scale bar is 10 μm; (d) 3D-SMART tracking of VSV-G Vpr-StayGold lentivirus in live 293T/17 cell^[109]; (e) bright-field image overlaid with the top-down view trajectory from (a); (f) fluorescence intensity traces from Fig. 17(a) compared with eGFP-labeled VLPs, demonstrating superior photostability and longer tracking duration of StayGold labeling

Fig. 18. Volumetric imaging of tumor spheroids with particle internalization tracking using the TSUNAMI ^[67]. (a) Three-dimensional isosurface rendering of a 100-µm diameter tumor spheroid; (b) isosurface model of the green cross-section in Fig. 18(a); (c) enlarged view of Fig. 18(b); (d) 3D reconstruction of isolated EGFR internalization trajectories; (e) instantaneous velocity plot over the duration of the trajectory

Fig. 19. Analysis of anti-EGFR IgG-conjugated anisotropic dimer landing behavior on plasma membrane^[68]. (a) 3D isosurface model of monolayer LNCaP cells; (b) local magnified view of dual-particle trajectories; (c) trajectory analysis in three typical time windows: I (0‒5 s), II (20‒25 s), and III (50‒55 s), corresponding to different interaction phases; (d) rose histograms quantitatively characterize the distribution patterns of azimuthal and elevation angles within respective time windows; (e) kinetic curves of angular variation (top) and translational diffusion coefficient (bottom) over time, with red dashed lines indicating critical transition time points

Fig. 20. Comparison of volumetric imaging scanning patterns between piezoelectric stage-based method and 3D-FASTR^[113]. (a)(c) 3D views of the scanning results after the first frame; (b)(d) 3D views of the scanning results after the last frame; (e)(f) differences in YZ plane scanning between the piezoelectric stage-based method and 3D-FASTR within a single frame time

Fig. 21. Tetrahedral detection-based three-dimensional tracking system^[123]. (a) Optical layout; (b) schematic of operation; (c) comparison of composite fluorescence lifetime traces with and without the quencher-labeled chain

Fig. 22. Schematic of 3D-SpecDIM^[139]. (a) 2D-EODs and TAG lens are used to drive the focused laser spot rapidly scanning in a small volume (1 μm×1 μm×2 μm) after objective; (b) FPGA utilizes the photon arrival time information collected by APD and the current laser position information to estimate the molecule's deviation from the center of illumination volume; (c) with the estimated molecule's deviation information, a feedback control voltage is applied to the piezoelectric stage to relocate the molecule to the center of illumination volume; (d) closed-loop feedback control; (e) synchronizing the 3D positional dynamics and the spectral dynamics enables multiparameter dynamics acquisition

Fig. 23. Single-particle dynamic light scattering characterizes the shape of individual metal nanoparticles by collecting polarization dynamic signals^[148]