KEYWORDS: Image restoration, Reconstruction algorithms, Detection and tracking algorithms, Image resolution, Image processing, Image enhancement, Confocal microscopy, Super resolution, Single photon detectors, Signal to noise ratio
Image Scanning Microscopy (ISM) enables super-resolution at an excellent signal-to-noise ratio thanks to a detector array. The microscope collects a confocal-like image for each detector element, generating a large dataset that requires tailored processing tools to be converted into a single super-resolved image. We propose a novel algorithm to fuse the dataset into an image with enhanced optical sectioning and resolution. Our method exploits the information inherently contained in the dataset to reject out-of-focus contributions and reconstruct an image with a smaller pixel size and a better resolution. The proposed method requires minimal user inputs and outperforms existing reconstruction methods.
In the recent years, numerous adaptive optics techniques have emerged to address optical aberrations in fluorescence microscopy imaging. However, many existing methods involve complex hardware implementations or lengthy iterative algorithms that may induce photo-damage to the sample. Our study proposes an innovative approach centered around a novel detector array capable of potentially capturing the probed sample in a single acquisition. Our solution is gentle on the sample and applicable to any laser scanning microscope equipped with a detector array. We demonstrate that the multi-dimensional dataset obtained using the detector array inherently encodes information about optical aberrations. Finally, we propose a convolutional neural network approach to decode these optical aberrations in real-time and with high accuracy, establishing the foundation for a new class of adaptive optics laser-scanning microscopy methods.
Fluorescence confocal laser-scanning microscopy (LSM) is one of the most popular tools for life science research. This popularity is expected to grow thanks to single-photon array detectors tailored for LSM. These detectors offer unique single-photon spatiotemporal information, opening new perspectives for gentle and quantitative superresolution imaging. However, a flawless recording of this information poses significant challenges for the microscope data acquisition (DAQ) system. We present a DAQ module based on the digital frequency domain principle, able to record essential spatial and temporal features of photons. We use this module to extend the capabilities of established imaging techniques based on single-photon avalanche diode (SPAD) array detectors, such as fluorescence lifetime image scanning microscopy. Furthermore, we use the module to introduce a robust multispecies approach encoding the fluorophore excitation spectra in the time domain. Finally, we combine time-resolved stimulated emission depletion microscopy with image scanning microscopy, boosting spatial resolution. Our results demonstrate how a conventional fluorescence laser scanning microscope can transform into a simple, information-rich, superresolved imaging system with the simple addition of a SPAD array detector with a tailored data acquisition system. We expected a blooming of advanced single-photon imaging techniques, which effectively harness all the sample information encoded in each photon.
Light-sheet microscopes with an extended depth of field (EDOF) offer a simple but powerful route toward fast volumetric imaging. However, methods for EDOF typically result in a loss of signal-to-noise ratio. Here, we propose a parallelization strategy as a simple solution. By illuminating multiple acoustically generated light sheets at different axial positions within the EDOF, and following an encoding sequence, information from several in-focus planes can be simultaneously retrieved. After applying a decoding algorithm, volumetric images are reconstructed with enhanced signal and level of detail. Our strategy paves the way for exploiting the full speed capabilities of EDOF light-sheet systems.
Bessel and annular laser beams offer intriguing possibilities for material processing. However, current beam shaping methods can be limited in tunability, speed, or parallelization possibilities. Here, we show how ultrasounds in liquids enable generating user-selectable arrays of Gaussian, Bessel-like, or annular beams. By cascading two liquid-filled acoustic cavities, each with a different geometry, light control can be achieved at microsecond time scales. Such an acousto-optic technology is easy to implement in current laser-direct writing workstations, providing an unprecedented ability to tune light fields based on application.
Laser-based systems are fundamental tools in several research and industrial fields as important as optical imaging and material processing. They grant high precision and flexibility, though, the throughput of these processes is constrained by their inherent point-scanning nature. An effective solution to this problem is beam parallelization, though, current implementations suffer from lack of flexibility, long response time or optical aberrations. In order to overcome these issues, we propose an original acousto-optofludic (AOF) device that exploits mechanical vibrations in a liquid to diffract light in a comb of multiple beams. In this work, we detail design, implementation, and optical characterization of AOF-based multi-focal laser system. In particular, we show that the main features of the acoustically generated beamlets can be tuned by properly varying frequency, amplitude, and phase of the mechanical oscillations. The application of this device to laser direct writing will enable high throughput processes of various materials in an highly tunable way.
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