High-fidelity intravital imaging of biological dynamics with latent-space-enhanced digital adaptive optics

Nasir-Moin, M. et al. Localization of protoporphyrin IX during glioma-resection surgery via paired stimulated Raman histology and fluorescence microscopy. Nat. Biomed. Eng. 8, 672–688 (2024).

Article  CAS  PubMed  Google Scholar 

Kanatani, S. et al. Whole-brain spatial transcriptional analysis at cellular resolution. Science 386, 907–915 (2024).

Article  CAS  PubMed  Google Scholar 

Sylwestrak, E. L., Rajasethupathy, P., Wright, M. A., Jaffe, A. & Deisseroth, K. Multiplexed intact-tissue transcriptional analysis at cellular resolution. Cell 164, 792–804 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ji, N. Adaptive optical fluorescence microscopy. Nat. Methods 14, 374–380 (2017).

Article  CAS  PubMed  Google Scholar 

Peng, B. et al. Practical guidelines for cell segmentation models under optical aberrations in microscopy. Comput. Struct. Biotechnol. J. 26, 23–39 (2024).

Article  PubMed  PubMed Central  Google Scholar 

Chen, W. et al. In vivo volumetric imaging of calcium and glutamate activity at synapses with high spatiotemporal resolution. Nat. Commun. 12, 6630 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hampson, K. M. et al. Adaptive optics for high-resolution imaging. Nat. Rev. Methods Prim. 1, 1–26 (2021).

Google Scholar 

Velasco, M. G. M. et al. 3D super-resolution deep-tissue imaging in living mice. Optica 8, 442–450 (2021).

Article  PubMed  PubMed Central  Google Scholar 

Wang, K. et al. Rapid adaptive optical recovery of optimal resolution over large volumes. Nat. Methods 11, 625–628 (2014).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Schubert, M. C. et al. Deep intravital brain tumor imaging enabled by tailored three-photon microscopy and analysis. Nat. Commun. 15, 7383 (2024).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Streich, L. et al. High-resolution structural and functional deep brain imaging using adaptive optics three-photon microscopy. Nat. Methods 18, 1253–1258 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kang, I., Zhang, Q., Yu, S. X. & Ji, N. Coordinate-based neural representations for computational adaptive optics in widefield microscopy. Nat. Mach. Intell. 6, 714–725 (2024).

Article  Google Scholar 

Hu, Q. et al. Universal adaptive optics for microscopy through embedded neural network control. Light Sci. Appl. 12, 270 (2023).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang, Y. et al. Conformal convolutional neural network (CCNN) for single-shot sensorless wavefront sensing. Opt. Express 28, 19218 (2020).

Article  PubMed  Google Scholar 

Guo, M. et al. Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy. Nat. Commun. 16, 313 (2025).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wu, J. et al. Iterative tomography with digital adaptive optics permits hour-long intravital observation of 3D subcellular dynamics at millisecond scale. Cell 184, 3318–3332 (2021).

Article  CAS  PubMed  Google Scholar 

Jogin, M. et al. Feature extraction using convolution neural networks (CNN) and deep learning. In Proc. 3rd International Conference on Recent Trends in Electronics, Information & Communication Technology https://doi.org/10.1109/RTEICT42901.2018.9012507 (IEEE, 2018).

Liang, H., Sun, X., Sun, Y. & Gao, Y. Text feature extraction based on deep learning: a review. EURASIP J. Wirel. Commun. Netw. 2017, 211 (2017).

Article  PubMed  PubMed Central  Google Scholar 

Shaheen, F., Verma, B. & Asafuddoula, M. D. Impact of automatic feature extraction in deep learning architecture. In Proc. International Conference on Digital Image Computing: Techniques and Applications https://doi.org/10.1109/DICTA.2016.7797053 (IEEE, 2016).

Chen, B. et al. Automated discovery of fundamental variables hidden in experimental data. Nat. Comput. Sci. 2, 433–442 (2022).

Article  PubMed  Google Scholar 

Higgins, I. et al. Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons. Nat. Commun. 12, 6456 (2021).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zhang, C. et al. A large, switchable optical clearing skull window for cerebrovascular imaging. Theranostics 8, 2696–2708 (2018).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Silasi, G., Xiao, D., Vanni, M. P., Chen, A. C. N. & Murphy, T. H. Intact skull chronic windows for mesoscopic wide-field imaging in awake mice. J. Neurosci. Methods 267, 141–149 (2016).

Article  PubMed  PubMed Central  Google Scholar 

de Haan, K., Rivenson, Y., Wu, Y. & Ozcan, A. Deep-learning-based image reconstruction and enhancement in optical microscopy. Proc. IEEE 108, 30–50 (2020).

Article  Google Scholar 

Reichstein, M. et al. Deep learning and process understanding for data-driven Earth system science. Nature 566, 195–204 (2019).

Article  CAS  PubMed  Google Scholar 

Mathieu, E., Rainforth, T., Siddharth, N. & Teh, Y. W. Disentangling disentanglement in variational autoencoders. In Proc. 36th International Conference on Machine Learning (eds Chaudhuri, K. & Sugiyama, M.) 4402–4412 (PMLR, 2019).

Brahma, P. P., Wu, D. & She, Y. Why deep learning works: a manifold disentanglement perspective. IEEE Trans. Neural Netw. Learn. Syst. 27, 1997–2008 (2016).

Article  PubMed  Google Scholar 

Zheng, Z. & Sun, L. Disentangling latent space for VAE by label relevant/irrelevant dimensions. In Proc. IEEE/CVF Conference on Computer Vision and Pattern Recognition 12192–12201 (2019).

Lu, Z. et al. Phase-space deconvolution for light field microscopy. Opt. Express 27, 18131–18145 (2019).

Article  PubMed  Google Scholar 

Liu, D. et al. T–B-cell entanglement and ICOSL-driven feed-forward regulation of germinal centre reaction. Nature 517, 214–218 (2015).

Article  CAS  PubMed  Google Scholar 

Mao, T. et al. Long-range neuronal circuits underlying the interaction between sensory and motor cortex. Neuron 72, 111–123 (2011).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Meiniel, W., Olivo-Marin, J.-C. & Angelini, E. D. Denoising of microscopy images: a review of the state-of-the-art, and a new sparsity-based method. IEEE Trans. Image Process. 27, 3842–3856 (2018).

Article  PubMed  Google Scholar 

Mandracchia, B. et al. Fast and accurate sCMOS noise correction for fluorescence microscopy. Nat. Commun. 11, 94 (2020).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Liang, C.-K., Lin, T.-H., Wong, B.-Y., Liu, C. & Chen, H. H. Programmable aperture photography: multiplexed light field acquisition. In ACM SIGGRAPH 2008 papers https://doi.org/10.1145/1399504.1360654 (ACM, 2008).

Prevedel, R. et al. Simultaneous whole-animal 3D imaging of neuronal activity using light-field microscopy. Nat. Methods 11, 727–730 (2014).

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lu, Z. et al. Long-term intravital subcellular imaging with confocal scanning light-field microscopy. Nat. Biotechnol. 43, 569–580 (2025).

Article  CAS  PubMed  Google Scholar 

Comments (0)

No login
gif