Structured detection for simultaneous super-resolution and optical sectioning in laser scanning microscopy

Fast detector arrays enable an effective implementation of image scanning microscopy, which overcomes the trade-off between spatial resolution and signal-to-noise ratio of confocal microscopy. However, current image scanning microscopy approaches do not provide optical sectioning and fail with thick samples unless the detector size is limited, thereby introducing a new trade-off between optical sectioning and signal-to-noise ratio. Here we propose a method that overcomes such a limitation. From single-plane acquisition, we reconstruct an image with digital and optical super-resolution, high signal-to-noise ratio and enhanced optical sectioning. On the basis of the observation that imaging with a detector array inherently embeds axial information, we designed a straightforward reconstruction algorithm that inverts the physical model of image scanning microscopy image formation. We present a comprehensive theoretical framework and validate our method with images of biological samples captured using a custom setup equipped with a single-photon avalanche diode array detector. We demonstrate the feasibility of our approach by exciting fluorescence emission in both linear and nonlinear regimes. Moreover, we generalize the algorithm for fluorescence lifetime imaging, fully exploiting the single-photon timing ability of the single-photon avalanche diode array detector. Our method outperforms conventional reconstruction techniques and can be extended to any laser scanning microscopy technique. A reconstruction method for image scanning microscopy exploits all the information encoded in the four-dimensional image scanning microscopy dataset to achieve optical sectioning and maintain super-resolution and high-signal-to-noise-ratio imaging.