Research progress on fast 3D fluorescence microscopic imaging (invited)
-
摘要: 荧光显微成像具有高分辨率、高灵敏度、高分子特异性以及非介入性的优点,可以在微米乃至纳米尺度下表征样本的形态学与分子功能学信息,成为了生命科学研究的重要工具。随着微观生物学研究的不断深入,荧光显微成像被期待能够动态且立体地观测微观生物结构与分子事件。文中系统性地梳理了近年来快速三维荧光显微成像技术的研究进展,包括点扫描式成像、宽场成像与投影断层成像在提高成像速度、拓展成像维度以及增强成像质量等方面的主要技术手段、改进策略与代表性研究成果,并展望了快速三维荧光显微成像技术的未来挑战与发展前景。Abstract: With the advantages of high resolution, high sensitivity, high molecule specificity and non-invasive, fluorescence microscopy can characterize the morphological and molecular functional information of samples at the micron or even nanometer scale, making it an important tool for life science research. As microbiology research continues to advance, fluorescence microscopy is expected to provide dynamic and 3D observation of microscopic biological structures and molecular events. This paper systematically reviews the research progress of fast 3D fluorescence microscopy in recent years, including the main technical means, improvement strategies and representative research results of point-scan imaging, wide-field imaging, and projection tomography to improve the imaging speed, expand the imaging dimension and enhance the imaging quality. In the end, we look forward to the future challenges and prospects of fast 3D fluorescence microscopic imaging techonology.
-
图 1 点扫描式系统结构示意图及其典型应用结果。(a) 激光共聚焦扫描显微镜结构图;(b) 脑组织切片的多色共聚焦图像及三维重建结果[24];(c) 单光子与双光子脑神经元体积成像,以及不同照明策略的成像深度[22]
Figure 1. Schematic diagram of the point-scanning system and its typical application results. (a) Structural diagram of confocal laser scanning microscope; (b) Multicolor confocal images and 3D reconstruction of brain tissue section[24]; (c) Single-photon and two-photon volumetric imaging of brain neurons, and imaging depths with different illumination strategies[22]
图 2 快速扫描技术的实现方式及其典型应用。(a) 多焦点扫描装置; (b) 转盘式多焦点扫描; (c) 快速扫描技术用于实时观测高尔基体的三维运动[31];(d) 时间延迟多焦点扫描;(e) 使用变焦透镜的轴向扫描;(f) 通过变焦透镜实现小鼠神 经元三维功能成像[32],180 µm×180 µm×165 µm,时间分辨率: 0.25 s;(g) 多焦点结构光照明显微镜对斑马鱼胚胎的 三维成像结果,红色框内是正在分裂的细胞[33]
Figure 2. Realization of fast scanning technology and its typical application. (a) Multifocal scanning device; (b) Spinning disk multifocal scanning; (c) Fast scanning technique for real-time observation of 3D movement of the Golgi apparatus[31]; (d) Time delayed multifocal scanning; (e) Axial scanning with tunable lens; (f) 3D functional imaging of mouse neurons through a tunable lens[32], 180 µm× 180 µm× 165 µm, temporal resolution: 0.25 s; (g) 3D imaging result of a zebrafish embryo through multifocal structured illumination microscope. Red box indicates a dividing cell[33]
图 3 光片显微镜结构及典型体积成像结果。(a) 传统光片显微镜的系统结构;(b) 斑马鱼心脏的体积成像结果[49], 包含二维图像序列(左)和三维重建结果(右),比例尺:50 μm;(c) 斑马鱼心脏随时间变化的图像[51],右侧折线图是心脏跳动动态,比例尺:30 μm
Figure 3. Structure of light-sheet microscope and typical volumetric imaging result. (a) Structure of traditional light-sheet microscope; (b) Volumetric imaging result of zebrafish heart[49], including 2D image sequence (left) and 3D reconstruction (right), scale bar: 50 μm; (c) Time-lapse images of a zebrafish heart[51], the line chart on the right is the heart beat dynamics, scale bar: 30 μm
图 4 光场显微镜结构及典型体积成像结果。(a) 传统光场显微镜的系统结构;(b) 蠕虫大脑不同深度的典型重建结果[59],比例尺:50 µm; (c) 200 Hz体积成像速率下的血流成像[60],200 µm×200 µm×200 µm
Figure 4. Structure of light-field microscope and typical volumetric imaging result. (a) Structure of traditional light-field microscope; (b) Typical reconstruction results at different depths of the worm brain[59], scale bar: 50 µm; (c) Blood flow imaging at 200 Hz volumetric imaging rate[60], 200 µm×200 µm×200 µm
图 5 三维结构光照明显微镜结构和超分辨技术典型成像结果。(a) 代表性系统结构;(b) 常规显微镜(左)和三维结构光照明显微镜(右)对荧光微球的成像结果对比[76];(c) 转铁蛋白簇的动态三维超分辨成像结果[80],比例尺:50 nm;(d) 大鼠海马神经元成像结果[81],包括宽场成像(左)、经典光学涨落超分辨重建(中)和使用傅里叶差值的光学涨落超分辨重建(右)
Figure 5. Structure of 3D-SIM and typical imaging result of super resolution technology. (a) Representative system structure; (b) Comparison of imaging results of fluorescent microspheres with conventional microscope (left) and 3D-SIM (right)[76]; (c) Dynamic 3D super resolution imaging results of transferrin clusters[80], scale bar: 50 nm; (d) Imaging results of rat hippocampal neuron[81], including widefield imaging (left), classical super resolution optical fluctuation reconstruction (middle), and super resolution optical fluctuation reconstruction using Fourier interpolation (right)
图 7 有限角度与稀疏采样的重建结果。(a) 180°和130°范围内断层重建结果[103];(b)滤波反投影法使用180个投 影数据的重建结果(左)和两阶段深度学习网络使用9 个投影数据的重建结果(右)[105]
Figure 7. Reconstruction results under limited angles or sparse sampling. (a) Results of 180° and 130° tomographic reconstruction[103]; (b) Reconstruction results of filtered back-projection using 180 projection data(left) and reconstruction results of 2-stage deep learning network using 9 projection data[105]
-
[1] Lakadamyali M. High resolution imaging of neuronal connec-tivity [J]. Journal of Microscopy, 2012, 248(2): 111-116. doi: 10.1111/j.1365-2818.2012.03638.x [2] Xu K, Babcock H P, Zhuang X W. Dual-objective STORM reveals three-dimensional filament organization in the actin cytoskeleton [J]. Nature Methods, 2012, 9(2): 185-188. doi: 10.1038/nmeth.1841 [3] Jungmann R, Avendano M S, Woehrstein J B, et al. Multiplexed 3D cellular super-resolution imaging with DNA-PAINT and exchange-PAINT [J]. Nature Methods, 2014, 11(3): 313-318. doi: 10.1038/nmeth.2835 [4] Lin J R, Fallahi-Sichani M, Sorger P K. Highly multiplexed imaging of single cells using a high-throughput cyclic immunofluorescence method [J]. Nature Communications, 2015, 6: 8390. doi: 10.1038/ncomms9390 [5] Peng X H, Huang X S, Du K, et al. High spatiotemporal resolution and low photo-toxicity fluorescence imaging in live cells and in vivo [J]. Biochemical Society Transactions, 2019, 47(6): 1635-1650. doi: 10.1042/bst20190020 [6] Kandel M E, He Y C R, Lee Y J, et al. Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments [J]. Nature Commu-nications, 2020, 11(1): 6256. doi: 10.1038/s41467-020-20062-x [7] Ghukasyan V V, Kao F J. Monitoring cellular metabolism with fluorescence lifetime of reduced nicotinamide adenine dinucleotide [J]. Journal of Physical Chemistry C, 2009, 113(27): 11532-11540. doi: 10.1021/jp810931u [8] Ouzounov D G, Wang T Y, Wang M R, et al. In vivo three-photon imaging of activity of GCaMP6-labeled neurons deep in intact mouse brain [J]. Nature Methods, 2017, 14(4): 388-390. doi: 10.1038/nmeth.4183 [9] Zhang X D, Wang H X, Wang H, et al. Single-layered graphitic-C3 N4 quantum dots for two-photon fluorescence imaging of cellular nucleus [J]. Advanced Materials, 2014, 26(26): 4438-4443. doi: 10.1002/adma.201400111 [10] von Diezmann A, Shechtman Y, Moerner W E. Three-dimensional localization of single molecules for super resolution imaging and single-particle tracking [J]. Chemical Reviews, 2017, 117(11): 7244-7275. doi: 10.1021/acs.chemrev.6b00629 [11] Hedde P N, Ranjit S, Gratton E. 3D fluorescence anisotropy imaging using selective plane illumination microscopy [J]. Optics Express, 2015, 23(17): 22308-22317. doi: 10.1364/oe.23.022308 [12] Wu Y, Wu X D, Lu R, et al. Resonant scanning with large field of view reduces photobleaching and enhances fluorescence yield in STED microscopy [J]. Scientific Reports, 2015, 5: 14766. doi: 10.1038/srep14766 [13] Palero J, Santos S, Artigas D, et al. A simple scanless two-photon fluorescence microscope using selective plane illumination [J]. Optics Express, 2010, 18(8): 8491-8498. doi: 10.1364/oe.18.008491 [14] Zhang Z K, Cong L, Bai L, et al. Light-field microscopy for fast volumetric brain imaging [J]. Journal of Neuroscience Methods, 2021, 352: 109083. doi: 10.1016/j.jneumeth.2021.109083 [15] Zhu L, Zhang W, Elnatan D, et al. Faster STORM using compressed sensing [J]. Nature Methods, 2012, 9(7): 721-723. doi: 10.1038/nmeth.1978 [16] Soini J T, Schrader M, Hanninen P E, et al. Image formation and data acquisition in a stage scanning 4Pi confocal fluorescence microscope [J]. Applied Optics, 1997, 36(34): 8929-8934. doi: 10.1364/ao.36.008929 [17] van Munster E B, Goedhart J, Kremers G J, et al. Combination of a spinning disc confocal unit with frequency-domain fluorescence lifetime imaging microscopy [J]. Cytometry Part A, 2007, 71A(4): 207-214. doi: 10.1002/cyto.a.20379 [18] Conchello J A, Lichtman J W. Optical sectioning microscopy [J]. Nature Methods, 2005, 2(12): 920-931. doi: 10.1038/nmeth815 [19] Qi X L, Yang T, Li L H, et al. Fluorescence micro-optical sectioning tomography using acousto-optical deflector-based confocal scheme [J]. Neurophotonics, 2015, 2(4): 041406. doi: 10.1117/1.NPh.2.4.041406 [20] Zong W J, Wu R L, Chen S Y, et al. Miniature two-photon microscopy for enlarged field-of-view, multi-plane and long-term brain imaging [J]. Nature Methods, 2021, 18(1): 46-49. doi: 10.1038/s41592-020-01024-z [21] Ruprecht A K, Wiesendanger T F, Tiziani H J. Chromatic confocal microscopy with a finite pinhole size [J]. Optics Letters, 2004, 29(18): 2130-2132. doi: 10.1364/ol.29.002130 [22] Ishii H, Otomo K, Takahashi T, et al. Focusing new light on brain functions: multiphoton microscopy for deep and super-resolution imaging [J]. Neuroscience Research, 2022, 179: 24-30. doi: 10.1016/j.neures.2021.11.011 [23] Arbabi E, Li J Q, Hutchins R J, et al. Two-photon microscopy with a double-wavelength metasurface objectivel ens [J]. Nano Letters, 2018, 18(8): 4943-4948. doi: 10.1021/acs.nanolett.8b01737 [24] Zhu S J, Yang Q L, Antaris A L, et al. Molecular imaging of biological systems with a clickable dye in the broad 800-to 1, 700-nm near-infrared window [J]. Proceedings of the National Academy of Sciences of the United States of America, 2017, 114(5): 962-967. doi: 10.1073/pnas.1617990114 [25] Yang W J, Carrillo-Reid L, Bando Y, et al. Simultaneous two-photon imaging and two-photon optogenetics of cortical circuits in three dimensions [J]. Elife, 2018, 7: e32671. doi: 10.7554/eLife.32671 [26] Scully A D, Ostler R B, MacRobert A J, et al. Laser line-scanning confocal fluorescence imaging of the photodynamic action of aluminum and zinc phthalocyanines in V79-4 Chinese hamster fibroblasts [J]. Photochemistry and Photobiology, 1998, 68(2): 199-204. doi: 10.1111/j.1751-1097.1998.tb02489.x [27] Piyawattanametha W, Barretto R P J, Ko T H, et al. Fast-scanning two-photon fluorescence imaging based on a microelectromechanical systems two-dimensional scanning mirror [J]. Optics Letters, 2006, 31(13): 2018-2020. doi: 10.1364/ol.31.002018 [28] Boutilier R M, Park J S, Lee H. High-speed two-photon laser scanning microscopy imaging of in vivo blood cells in rapid circulation at velocities of up to 1.2 millimeters per second [J]. Current Optics and Photonics, 2018, 2(6): 595-605. doi: 10.3807/copp.2018.2.6.595 [29] Zhang T, Hernandez O, Chrapkiewicz R, et al. Kilohertz two-photon brain imaging in awake mice [J]. Nature Methods, 2019, 16(11): 1119-1122. doi: 10.1038/s41592-019-0597-2 [30] Woods E, Courtney J, Scholz D, et al. Tracking protein dynamics with photoconvertible Dendra2 on spinning disk confocal systems [J]. Journal of Microscopy, 2014, 256(3): 197-207. doi: 10.1111/jmi.12172 [31] Oketani R, Suda H, Uegaki K, et al. Visible-wavelength two-photon excitation microscopy with multifocus scanning for volumetric live-cell imaging [J]. Journal of Biomedical Optics, 2020, 25(1): 014502. doi: 10.1117/1.Jbo.25.1.014502 [32] Chien Y F, Lin J Y, Yeh P T, et al. Dual GRIN lens two-photon endoscopy for high-speed volumetric and deep brain imaging [J]. Biomedical Optics Express, 2021, 12(1): 162-172. doi: 10.1364/boe.405738 [33] York A G, Parekh S H, Nogare D D, et al. Resolution doubling in live, multicellular organisms via multifocal structured illumination microscopy [J]. Nature Methods, 2012, 9(7): 749-754. doi: 10.1038/nmeth.2025 [34] Chen Z Y, Mc Larney B, Rebling J, et al. High-speed large-field multifocal illumination fluorescence microscopy [J]. Laser & Photonics Reviews, 2020, 14(2): 1900070. doi: 10.1002/lpor.201900070 [35] Wu J L, Liang Y J, Chen S, et al. Kilohertz two-photon fluorescence microscopy imaging of neural activity in vivo [J]. Nature Methods, 2020, 17(3): 287-290. doi: 10.1038/s41592-020-0762-7 [36] Duocastella M, Sun B, Arnold C B. Simultaneous imaging of multiple focal planes for three-dimensional microscopy using ultra-high-speed adaptive optics [J]. Journal of Biomedical Optics, 2012, 17(5): 050505. doi: 10.1117/1.Jbo.17.5.050505 [37] Weisenburger S, Tejera F, Demas J, et al. Volumetric Ca2+ imaging in the mouse brain using hybrid multiplexed sculpted light microscopy [J]. Cell, 2019, 177(4): 1050-1066. doi: 10.1016/j.cell.2019.03.011 [38] Lu R W, Liang Y J, Meng G H, et al. Rapid mesoscale volumetric imaging of neural activity with synaptic resolution [J]. Nature Methods, 2020, 17(3): 291-294. doi: 10.1038/s41592-020-0760-9 [39] Hao X, Li Y M, Fu S, et al. Review of 4Pi fluorescence nanoscopy [J]. Engineering, 2022, 11: 146-153. doi: 10.1016/j.eng.2020.07.028 [40] Tortarolo G, Sun Y S, Teng K W, et al. Photon-separation to enhance the spatial resolution of pulsed STED microscopy [J]. Nanoscale, 2019, 11(4): 1754-1761. doi: 10.1039/c8nr07485b [41] Velasco M G M, Zhang M Y, Antonello J, et al. 3D super-resolution deep-tissue imaging in living mice [J]. Optica, 2021, 8(4): 442-450. doi: 10.1364/optica.416841 [42] Li B, Wu C Y, Wang M R, et al. An adaptive excitation source for high-speed multiphoton microscopy [J]. Nature Methods, 2020, 17(2): 163-166. doi: 10.1038/s41592-019-0663-9 [43] Hillman E M C, Voleti V, Li W Z, et al. Light-sheet microscopy in neuroscience[M]//Annual Review of Neuro-science, 2019. [44] Gibbs H C, Mota S M, Hart N A, et al. Navigating the light-sheet image analysis software landscape: concepts for driving cohesion from data acquisition to analysis [J]. Frontiers in Cell and Developmental Biology, 2021, 9: 739079. doi: 10.3389/fcell.2021.739079 [45] Poola P K, Afzal M I, Yoo Y, et al. Light sheet microscopy for histopathology applications [J]. Biomedical Engineering Letters, 2019, 9(3): 279-291. doi: 10.1007/s13534-019-00122-y [46] Gu P C, Huang Z X, Ping M, et al. Thinner and longer working distance light sheet illumination and microscopic imaging [J]. IEEE Journal of Selected Topics in Quantum Electronics, 2021, 27(4): 7300107. doi: 10.1109/jstqe.2020.2996606 [47] Liu T L, Upadhyayula S, Milkie D E, et al. Observing the cell in its native state: Imaging subcellular dynamics in multicellular organisms [J]. Science, 2018, 360(6386): 284-284. doi: 10.1126/science.aaq1392 [48] Fei P, Nie J, Lee J, et al. Subvoxel light-sheet microscopy for high-resolution high-throughput volumetric imaging of large biomedical specimens [J]. Advanced Photonics, 2019, 1(1): 016002. doi: 10.1117/1.AP.1.1.016002 [49] Fahrbach F O, Voigt F F, Schmid B, et al. Rapid 3D light-sheet microscopy with a tunable lens [J]. Optics Express, 2013, 21(18): 21010-21026. doi: 10.1364/oe.21.021010 [50] Haslehurst P, Yang Z Y, Dholakia K, et al. Fast volume-scanning light sheet microscopy reveals transient neuronal events [J]. Biomedical Optics Express, 2018, 9(5): 2154-2167. doi: 10.1364/boe.9.002154 [51] Lin P Y, Hwang S P L, Lee C H, et al. Two-photon scanned light sheet fluorescence microscopy with axicon imaging for fast volumetric imaging [J]. Journal of Biomedical Optics, 2021, 26(11): 116503. doi: 10.1117/1.Jbo.26.11.116503 [52] Olarte O E, Andilla J, Artigas D, et al. Decoupled illumination detection in light sheet microscopy for fast volumetric imaging [J]. Optica, 2015, 2(8): 702-705. doi: 10.1364/optica.2.000702 [53] Yang B, Chen X Y, Wang Y N, et al. Epi-illumination SPIM for volumetric imaging with high spatial-temporal resolution [J]. Nature Methods, 2019, 16(6): 501-504. doi: 10.1038/s41592-019-0401-3 [54] Yang B, Lange M, Millett-Sikking A, et al. DaXi-high-resolution, large imaging volume and multi-view single-objective light-sheet microscopy [J]. Nature Methods, 2022, 19(4): 461-469. doi: 10.1038/s41592-022-01417-2 [55] Cai Y H, Chen Y Z, Xia Y Q, et al. Single-lens light-sheet fluorescence microscopy based on micro-mirror array [J]. Laser & Photonics Reviews, 2022, 16(8): 2100026. doi: 10.1002/lpor.202100026 [56] Wang D P, Zhu Z J, Xu Z Y, et al. Neuroimaging with light field microscopy: a mini review of imaging systems [J]. European Physical Journal-Special Topics, 2022, 231(4): 749-761. doi: 10.1140/epjs/s11734-021-00367-8 [57] Broxton M, Grosenick L, Yang S, et al. Wave optics theory and 3-D deconvolution for the light field microscope [J]. Optics Express, 2013, 21(21): 25418-25439. doi: 10.1364/oe.21.025418 [58] Wang D P, Roy S, Rudzite A M, et al. High-resolution light-field microscopy with patterned illumination [J]. Biomedical Optics Express, 2021, 12(7): 3887-3901. doi: 10.1364/boe.425742 [59] Prevedel R, Yoon Y G, Hoffmann M, et al. Simultaneous whole-animal 3D imaging of neuronal activity using light-field microscopy [J]. Nature Methods, 2014, 11(7): 727-730. doi: 10.1038/nmeth.2964 [60] Wagner N, Norlin N, Gierten J, et al. Instantaneous isotropic volumetric imaging of fast biological processes [J]. Nature Methods, 2019, 16(6): 497-500. doi: 10.1038/s41592-019-0393-z [61] Wu J M, Lu Z, Jian D, et al. Iterative tomography with digital adaptive optics permits hour-long intravital observation of 3D subcellular dynamics at millisecond scale [J]. Cell, 2021, 184(12): 3318-3332.e17. doi: 10.1016/j.cell.2021.04.029 [62] Pan Z, Lu M, Xia S. Diffraction-assisted light field microscopy for microtomography and digital volume correlation with improved spatial resolution [J]. Experimental Mechanics, 2019, 59(5): 713-724. doi: 10.1007/s11340-019-00522-2 [63] He K, Wang X L, Wang Z H W, et al. Snapshot multifocal light field microscopy [J]. Optics Express, 2020, 28(8): 12108-12120. doi: 10.1364/oe.390719 [64] Geng Q, Fu Z Q, Chen S C. High-resolution 3D light-field imaging [J]. Journal of Biomedical Optics, 2020, 25(10): 106502. doi: 10.1117/1.Jbo.25.10.106502 [65] Wang Z Q, Zhu L X, Zhang H, et al. Real-time volumetric reconstruction of biological dynamics with light-field microscopy and deep learning [J]. Nature Methods, 2021, 18(5): 551-556. doi: 10.1038/s41592-021-01058-x [66] Liu J D, Xu T F, Yue W R, et al. Light-field moment microscopy with noise reduction [J]. Optics Express, 2015, 23(22): 29154-29162. doi: 10.1364/oe.23.029154 [67] Wang H C, Chen N, Zheng S S, et al. Fast and high-resolution light field acquisition using defocus modulation [J]. Applied Optics, 2018, 57(1): A250-A256. doi: 10.1364/ao.57.00a250 [68] Truong T V, Holland D B, Madaan S, et al. High-contrast, synchronous volumetric imaging with selective volume illumination microscopy [J]. Communications Biology, 2020, 3(1): 74. doi: 10.1038/s42003-020-0787-6 [69] Wang D P, Xu S, Pant P, et al. Hybrid light-sheet and light-field microscope for high resolution and large volume neuroimaging [J]. Biomedical Optics Express, 2019, 10(12): 6595-6610. doi: 10.1364/boe.10.006595 [70] Zhang Z K, Bai L, Cong L, et al. Imaging volumetric dynamics at high speed in mouse and zebrafish brain with confocal light field microscopy [J]. Nature Biotechnology, 2021, 39(1): 74-83. doi: 10.1038/s41587-020-0628-7 [71] Schneckenburger H, Richter V. Laser scanning versus wide-field-choosing the appropriate microscope in life sciences [J]. Applied Sciences-Basel, 2021, 11(2): 733. doi: 10.3390/app11020733 [72] Luo J T, Li C K, Liu Q L, et al. Super-resolution structured illumination microscopy reconstruction using a least-squares solver [J]. Frontiers in Physics, 2020, 8: 118. doi: 10.3389/fphy.2020.00118 [73] Leung B O, Chou K C. Review of super-resolution fluorescence microscopy for biology [J]. Applied Spectroscopy, 2011, 65(9): 967-980. doi: 10.1366/11-06398 [74] Kurdzialek S, Demkowicz-Dobrzanski R. Super-resolution optical fluctuation imaging-fundamental estimation theory perspective [J]. Journal of Optics, 2021, 23(7): 075701. doi: 10.1088/2040-8986/ac059c [75] Prakash K, Diederich B, Reichelt S, et al. Super-resolution structured illumination microscopy: past, present and future [J]. Philosophical Transactions of the Royal Society A-Mathematical Physical and Engineering Sciences, 2021, 379(2199): 20200143. doi: 10.1098/rsta.2020.0143 [76] Gustafsson M G L, Shao L, Carlton P M, et al. Three-dimensional resolution doubling in wide-field fluorescence microscopy by structured illumination [J]. Biophysical Journal, 2008, 94(12): 4957-4970. doi: 10.1529/biophysj.107.120345 [77] Fiolka R, Beck M, Stemmer A. Structured illumination in total internal reflection fluorescence microscopy using a spatial light modulator [J]. Optics Letters, 2008, 33(14): 1629-1631. doi: 10.1364/ol.33.001629 [78] Schwertner M, Booth M J, Wilson T. Specimen-induced distortions in light microscopy [J]. Journal of Microscopy, 2007, 228(1): 97-102. doi: 10.1111/j.1365-2818.2007.01827.x [79] Lin R Z, Kipreos E T, Zhu J, et al. Subcellular three-dimensional imaging deep through multicellular thick samples by structured illumination microscopy and adaptive optics [J]. Nature Communications, 2021, 12(1): 3148. doi: 10.1038/s41467-021-23449-6 [80] Jones S A, Shim S H, He J, et al. Fast, three-dimensional super-resolution imaging of live cells [J]. Nature Methods, 2011, 8(6): 499-505. doi: 10.1038/nmeth.1605 [81] Stein S C, Huss A, Hahnel D, et al. Fourier interpolation stochastic optical fluctuation imaging [J]. Optics Express, 2015, 23(12): 16154-16163. doi: 10.1364/oe.23.016154 [82] Samanta S, Gong W J, Li W, et al. Organic fluorescent probes for stochastic optical reconstruction microscopy (STORM): Recent highlights [J]. Coordination Chemistry Reviews, 2019, 380: 17-34. doi: 10.1016/j.ccr.2018.08.006 [83] Lelek M, Gyparaki M, Melina T, et al. Single-molecule localization microscopy [J]. Nature Reviews Methods Primers, 2021, 1: 39. doi: 10.1038/s43586-021-00038-x [84] Huang B, Wang W Q, Bates M, et al. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy [J]. Science, 2008, 319(5864): 810-813. doi: 10.1126/science.1153529 [85] Wang Y H, Jia S, Zhang H F, et al. Blind sparse inpainting reveals cytoskeletal filaments with sub-Nyquist localization [J]. Optica, 2017, 4(10): 1277-1284. doi: 10.1364/optica.4.001277 [86] Zeng Z P, Chen X Z, Wang H N, et al. Fast super-resolution imaging with ultra-high labeling density achieved by joint tagging super-resolution optical fluctuation imaging [J]. Scientific Reports, 2015, 5: 8359. doi: 10.1038/srep08359 [87] GruSsmayer K S, Geissbuehler S, Descloux A, et al. Spectral cross-cumulants for multicolor super-resolved SOFI imaging [J]. Nature Communications, 2020, 11(1): 3023. doi: 10.1038/s41467-020-16841-1 [88] Chen X Z, Zeng Z P, Li R Q, et al. Superior performance with sCMOS over EMCCD in super-resolution optical fluctuation imaging [J]. Journal of Biomedical Optics, 2016, 21(6): 066007. doi: 10.1117/1.Jbo.21.6.066007 [89] Sharpe J. Optical projection tomography [J]. Annual Review of Biomedical Engineering, 2004, 6: 209-228. doi: 10.1146/annurev.bioeng.6.040803.140210 [90] Birk U J, Rieckher M, Konstantinides N, et al. Correction for specimen movement and rotation errors for in-vivo optical projection tomography [J]. Biomedical Optics Express, 2010, 1(1): 87-96. doi: 10.1364/boe.1.000087 [91] Vinegoni C, Fexon L, Feruglio P F, et al. High throughput transmission optical projection tomography using low cost graphics processing unit [J]. Optics Express, 2009, 17(25): 22320-22332. doi: 10.1364/oe.17.022320 [92] Bassi A, Fieramonti L, D'Andrea C, et al. In vivo label-free three-dimensional imaging of zebrafish vasculature with optical projection tomography [J]. Journal of Biomedical Optics, 2011, 16(10): 100502. doi: 10.1117/1.3640808 [93] Arranz A, Dong D, Zhu S P, et al. In-vivo optical tomography of small scattering specimens: time-lapse 3D imaging of the head eversion process in Drosophila melanogaster [J]. Scientific Reports, 2014, 4: 7325. doi: 10.1038/srep07325 [94] McGinty J, Taylor H B, Chen L, et al. In vivo fluorescence lifetime optical projection tomography [J]. Biomedical Optics Express, 2011, 2(5): 1340-1350. doi: 10.1364/boe.2.001340 [95] Juntunen C, Woller I M, Sung Y J. Hyperspectral three-dimensional fluorescence imaging using snapshot Optical Tomography [J]. Sensors, 2021, 21(11): 3652. doi: 10.3390/s21113652 [96] Sharpe J, Ahlgren U, Perry P, et al. Optical projection tomography as a tool for 3D microscopy and gene expression studies [J]. Science, 2002, 296(5567): 541-545. doi: 10.1126/science.1068206 [97] Zhu S P, Dong D, Birk U J, et al. Automated motion correction for in vivo optical projection tomography [J]. IEEE Transactions on Medical Imaging, 2012, 31(7): 1358-1371. doi: 10.1109/tmi.2012.2188836 [98] Cheddad A, Svensson C, Sharpe J, et al. Image processing assisted algorithms for optical projection tomography [J]. IEEE Transactions on Medical Imaging, 2012, 31(1): 1-15. doi: 10.1109/tmi.2011.2161590 [99] Chen L L, McGinty J, Taylor H B, et al. Incorporation of an experimentally determined MTF for spatial frequency filtering and deconvolution during optical projection tomography reconstruction [J]. Optics Express, 2012, 20(7): 7323-7337. doi: 10.1364/oe.20.007323 [100] Gong C C, Zeng L, Wang C X. Image reconstruction model for limited-angle CT based on prior image induced relative total variation [J]. Applied Mathematical Modelling, 2019, 74: 586-605. doi: 10.1016/j.apm.2019.05.020 [101] Gong C C, Zeng L. Anisotropic structure property based image reconstruction method for limited-angle computed tomography [J]. Journal of X-Ray Science and Technology, 2021, 29(6): 1079-1102. doi: 10.3233/xst-210954 [102] Chen Z Q, Jin X, Li L, et al. A limited-angle CT reconstruction method based on anisotropic TV minimization [J]. Physics in Medicine and Biology, 2013, 58(7): 2119-2141. doi: 10.1088/0031-9155/58/7/2119 [103] Wang N, Chen D F, Chen D, et al. Feasibility study of limited-angle reconstruction for in vivo optical projection tomography based on novel sample fixation [J]. IEEE Access, 2019, 7: 87681-87691. doi: 10.1109/access.2019.2925096 [104] Chen X L, Zhu S P, Wang H Y, et al. Accelerated stimulated Raman projection tomography by sparse reconstruction from sparse-view data [J]. IEEE Transactions on Biomedical Engineering, 2020, 67(5): 1293-1302. doi: 10.1109/tbme.2019.2935301 [105] Wang H Y, Wang N, Xie H, et al. Two-stage deep learning network-based few-view image reconstruction for parallel-beam projection tomography [J]. Quantitative Imaging in Medicine and Surgery, 2022, 12(4): 2535-2551. doi: 10.21037/qims-21-778 [106] Zhong Q Y, Li A A, Jin R, et al. High-definition imaging using line-illumination modulation microscopy [J]. Nature Methods, 2021, 18(3): 309-315. doi: 10.1038/s41592-021-01074-x [107] Zhu S J, Herraiz S, Yue J Y, et al. 3D NIR-II molecular imaging distinguishes targeted organs with high-performance NIR-II bioconjugates [J]. Advanced Materials, 2018, 30(13): 1705799. doi: 10.1002/adma.201705799 [108] Rodriguez C, Chen A, Rivera J A, et al. An adaptive optics module for deep tissue multiphoton imaging in vivo [J]. Nature Methods, 2021, 18(10): 1259-1264. doi: 10.1038/s41592-021-01279-0 [109] Fan J T, Suo J L, Wu J M, et al. Video-rate imaging of biological dynamics at centimetre scale and micrometre resolution [J]. Nature Photonics, 2019, 13(11): 809-816. doi: 10.1038/s41566-019-0474-7 [110] Ozeki Y, Umemura W, Otsuka Y, et al. High-speed molecular spectral imaging of tissue with stimulated Raman scattering [J]. Nature Photonics, 2012, 6(12): 844-850. doi: 10.1038/nphoton.2012.263 [111] Chen X L, Zhang C, Lin P, et al. Volumetric chemical imaging by stimulated Raman projection microscopy and tomography [J]. Nature Communications, 2017, 8: 15117. doi: 10.1038/ncomms15117