In vivo fluorescence imaging in the second near-infrared window (NIR-II) has been considered as a promising technique for visualizing mammals. However, the definition of the NIR-II region and the mechanism accounting for the excellent performance still need to be perfected. Herein, we simulate the photon propagation in the NIR region (to 2340 nm), confirm the positive contribution of moderate light absorption by water in intravital imaging and perfect the NIR-II window as 900–1880 nm, where 1400–1500 and 1700–1880 nm are defined as NIR-IIx and NIR-IIc regions, respectively. Moreover, 2080–2340 nm is newly proposed as the third near-infrared (NIR-III) window, which is believed to provide the best imaging quality. The wide-field fluorescence microscopy in the brain is performed around the NIR-IIx region, with excellent optical sectioning strength and the largest imaging depth of intravital NIR-II fluorescence microscopy to date. We also propose 1400 nm long-pass detection in off-peak NIR-II imaging whose performance exceeds that of NIR-IIb imaging, using bright fluorophores with short emission wavelength.

Many applications requiring both spectral and spatial information at high resolution benefit from spectral imaging. Although different technical methods have been developed and commercially available, computational spectral cameras represent a compact, lightweight, and inexpensive solution. However, the tradeoff between spatial and spectral resolutions, dominated by the limited data volume and environmental noise, limits the potential of these cameras. In this study, we developed a deeply learned broadband encoding stochastic hyperspectral camera. In particular, using advanced artificial intelligence in filter design and spectrum reconstruction, we achieved 7000–11,000 times faster signal processing and ~10 times improvement regarding noise tolerance. These improvements enabled us to precisely and dynamically reconstruct the spectra of the entire field of view, previously unreachable with compact computational spectral cameras.

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