Fig. 1. Contrast of the optics components and light propagation for LFM and FLFM^[7]. (a) Traditional LFM; (b) FLFM

Fig. 2. Lateral resolution analysis of FLFM^[7]

Fig. 3. Axial resolution analysis of FLFM^[7]

Fig. 4. Field of view analysis of FLFM^[7]

Fig. 5. Depth of field analysis of FLFM^[7]. (a) Based on axial diffraction of light to determine depth of field; (b) based on the light-field pattern at varying depths to determine depth of field

Fig. 6. PSF contrast of FLFM and LFM. Contrast of the simulated and experimental PSF for FLFM (a) and LFM (b)^[7]; (c) simulated PSF of HR-LFM^[11]; (d) light field PSF modeled based on wave optics modeling^[2]; (e) simulated PSF of improved SMLFM^[10]; (f) simulated PSF of hPSF-FLFM^[12]

Fig. 7. FLFM subcellular imaging. (a)‒(c) Schematic structure of HR-FLFM system and reconstruction results^[20]; (d)‒(e) HR-FLFM for autofluorescence reconstruction of organelle dynamic processes^[21]; (f)‒(h) system structure of rad-FLFM and reconstruction results^[22]; (i)‒(l) SMLFM reconstruction results and analysis^[10,23]; (m)‒(p) SOFFLFM reconstruction results^[24]

Fig. 8. LFC organoid imaging display^[32]. (a)‒(b) Main design of LFC system; (c)‒(l) reconstructed results and analysis of LFC system

Fig. 9. EventLFM imaging procedure and Caenorhabditis elegans imaging^[39]. (a) Schematic of EventLFM imaging and reconstruction workflow; (b) image of Caenorhabditis elegans captured using traditional wide-field fluorescence microscopy; (c) MIP of depth-color-coded reconstructed volume after EventLFM reconstruction

Fig. 10. Organoid imaging via FLFM. (a)‒(l) hPSF-FLFM reconstructed images of organoids under the environment of osmotic pressure changes and external force^[12]; (m)‒(n) FLFM reconstructed images of cardiac spheroids cultured on the ground and in aerial flights with Callbryte 520 a.m. Ca²⁺ indicator^[49]

Fig. 11. Structure of XLFM, confocal FLFM, and SLIM, as well as their imaging of zebrafish. (a) XLFM imaging system for free-swimming zebrafish larvae^[55]; (b) full-brain calcium activity renderings (top) of zebrafish larvae preying on paramecia at six time points, with corresponding behavioral images (bottom)^[55]; (c) MIP of the zebrafish brain using pan-neuronal cytoplasmic GCaMP6s^[55]; (d) neuronal dynamics inferred from GCaMP6s fluorescence changes during the entire preying behavior, and behavioral feature dynamics^[55]; (e) schematic of the confocal FLFM system^[56]; (f) comparison of MIP images within the shown axial range at representative time points before and after successful paramecium capture^[56]; (g) schematic of SLIM detection system^[57]; (h) 3D imaging of hemodynamics in the brain and tail of embryonic zebrafish^[57]

Fig. 12. Schematic diagrams of MSR algorithm flow^[60]. (a) Schematic diagram of FLFM optical structure; (b) flow diagram of MSR

Fig. 13. MSR-processed FLFM imaging of Xenopus cardiac and vascular system^[60]. (a)‒(d) Results and analysis of 3D depth-color-coded MSR reconstruction of GFP-labelled cardiomyocyte nuclei; (e)‒(i) time series analysis of MSR reconstructed blood vessels

Fig. 14. Imaging of the mouse brain using RFLFM and confocal scanning LFM. (a) RFLFM system structure^[62]; (b)‒(e) RFLFM reconstruction results and analysis^[62], with color-coded depth of [-45, 45] μm and scale bar of 100 μm in (b) and (c); (f) schematic diagram of the structure of confocal scanning LFM^[63]; (g)‒(h) analysis of confocal scanning LFM imaging results^[63], left image scale in (g): 100 µm, right image scale: 25 µm

Fig. 15. F-VCD and Deep-SMLFM reconstruction process and imaging results. (a) F-VCD model to perform real-time 3D image inference from recorded 2D light field images^[66]; (b)‒(d) comparative demonstration of reconstruction effect of F-VCD and other methods^[66]; (e)‒(g) Deep-SMLFM system architecture and general processing flow^[71]; (h)‒(j) analysis of Deep-SMLFM reconstruction results^[71], scale bar: 10 μm