Fig. 1. Mechanism of OCT imaging and 3D reconstruction.（a）Schematic diagram of spectral domain OCT（SD-OCT）imaging^［13];(b) reconstruction of 3D OCT image for mouse full eye in vivo^{[13, 15]}

Fig. 2. Lens-free probe with tunable output beam^[20]. (a) Layout of probe; (b) two-dimensional light intensity distribution of outgoing beam under four typical parameters; (c) photograph and micrograph of fabricated probe; (d) image of human finger from probe-based OCT system; (e) image of human finger from galvanometer desktop system

Fig. 3. Schematic diagram of principle for generating OCTA

Fig. 4. Asymptotic relation of ID and generated OCTA images^[50]. (a) Asymptotic relation of ID; (b) image of ICP in mouse eye; (c) image of choroid in mouse eye; (d) image of whole retina in mouse eye; (e) image of SVP in mouse eye; (f) image of DCP in mouse eye; (g) image of whole retina in human eye; (h) image of SVP in human eye; (i) image of DCP in human eye

Fig. 5. FLS-evoked hemodynamic responses of mouse retina in vivo^[54]. (a) OCTA projection of baseline phase in decorrelation coded SVP; (b) OCTA projection of baseline phase in decorrelation coded ICP; (c) OCTA projection of baseline phase in decorrelation coded DCP; (d) OCTA projection of FLS phase in decorrelation coded SVP; (e) OCTA projection of FLS phase in decorrelation coded ICP; (f) OCTA projection of FLS phase in decorrelation coded DCP; (g) quantitative monitoring curve of vascular morphology; (h) quantitative monitoring curve of decorrelation coefficient in blood flow area

Fig. 6. OCTA-based OAC measurement and correlation between OAC and BGC^[41]. (a) OAC projection of retinal arteries and veins for healthy mice; (b) OAC projection of retinal arteries and veins for diabetic mice; (c) correlation curve of OAC and BGC for retinal arterioles; (d) correlation curve of OAC and BGC for retinal venules

Fig. 7. OCTA imaging of buccal mucosa by ET MEMS-based distal-end scanning probe^[61]. (a) Three-dimensional images of fused OCT structure (gray) and OCTA vasculature (yellow) in buccal mucosa; (b) projection of maximum OCTA of pLP layer in buccal mucosa; (c) projection of maximum OCTA of rLP layer in buccal mucosa

Fig. 8. Three-photon fluorescence imaging of cerebral blood vessels, neuronal structures and brain functions. (a) Three-photon fluorescence imaging of three-dimensional structures of cerebral blood vessels and cranial nerves in mice^[3]; (b) three-photon fluorescence functional neuronal imaging under craniotomy window in mice^[65]; (c) three-photon fluorescence neuronal functional imaging of mice with intact skulls^[66]

Fig. 9. Various three-photon fluorescence imaging applications. (a) Maximum-depth three-photon fluorescence imaging for structures of cerebral blood vessels in mice^[69]; (b) three-photon fluorescence lifetime imaging of cerebral blood vessels in mice^[73]; (c) three-photon photodynamic therapy of HeLa cells^[74]; (d) three-photon fluorescence imaging for observation of lipid droplet morphology in mouse fatty liver^[75]; (e) three-dimensional structural imaging of intact lymph nodes in mice by three-photon fluorescence imaging ^[76]

Fig. 10. Three-photon fluorescence imaging depth and imaging speed improved by adaptive optics. (a) Schematic diagram of mobile-correlated adaptive-optics three-photon microscopy^[77]; (b) three-photon fluorescence structural imaging of mouse brain neurons under adaptive-optics three-photon fluorescence microscopy^[77]; (c) principle of adaptive excitation source improving speed of three-photon fluorescence imaging^[83]; (d) signal-to-background ratio significantly improved by adaptive excitation source during neuronal structural and functional recording process^[83]

Fig. 11. Two AO modes^[86]

Fig. 12. Principle of SH sensor^[89]

Fig. 13. Optical aberration corrector^[86]

Fig. 14. Wavefront detection comparison^[105]

Fig. 15. Reconstructed SIM images of Phalloidin labeled actin in cultured baby hamster Syrian kidney cells^[106]. (a) Before AO correction; (b) after AO correction; (c) intensity profiles of dotted lines in Fig. 15(a) and Fig. 15(b)

Fig. 16. Image enhancement performance of SRACNet on confocal microscopy^[107]

Fig. 17. Comparison of wavefront sensing capability of TSHWS and LSHWS^[108]. (a) Distorted SHWS pattern; (b) SHWS pattern compensated by wavefront detected by TSHWS; (c) SHWS pattern compensated by wavefront detected by LSHWS; (d) comparison of numbered spots in Figs. 17(a)-(c); (e) aberration wavefront, TSHWS detected wavefront and LSHWS detected wavefront; (f) comparison of spot intensity distribution in Figs. 17(a)-(c)

Fig. 18. Definition of spatial orientation for fiber-like structures^[120]. (a) Definition of angles in orientation of three-dimensional space fiber-like structure; (b) schematic diagram of weighted vector summation algorithm; (c) spatial orientation obtained by summing weighted vectors; (d) θ orientation map for plane marked in green in Fig. 18(a); (e) φ orientation map for plane marked in blue in Fig. 18(a); (f) three-dimensional directional variance acquired by three-dimensional spatial orientation

Fig. 19. Schematic diagram of paWav calculation for fiber-like structures^[123]. (a) Flow chart of paWav algorithm; (b) extension of paWav algorithm from two-dimensional format to three-dimensional format; (c) raw intensity, spatial orientation, directional variance, and paWav maps of blood vessels in mice

Fig. 20. New endoplasmic reticulum growth mechanism named Hooking^[124]

Fig. 21. Schematic diagram of generation and recovery of photothrombotic obstruction^[125]. (a) Schematic diagram of laser-induced cerebrovascular thrombosis in mice; thickness characterization results of cerebrovascular at different time points (b) before and (c) after photothrombotic obstruction, with white dashed circles indicating choked regions; (d) corresponding thickness maps of blood vessels, with one slight obstruction flushed away due to high-speed blood flow; (e) thickness quantification results of corresponding regions, with both slight obstructions flushed away by blood flow