Hidden phase-retrieved fluorescence tomography

Removal of algorithmic stagnation by augmented iterative phase retrieval

Retrieving the phase of an optical field using intensity measurements is one of the most widespread and studied inverse problems in classical optics. However, common iterative approaches such as the Gerchberg-Saxton algorithm and its derivatives suffer from the twin-image problem - the iterative minimisation stagnates and the recovered field contains features from both the target field and its point-reflection. We present a technique that leverages mathematical properties of the stagnated field, to constrain the problem and remove the twin image artefacts. This improvement in reconstruction robustness has implications in a range of fields, including applications in adaptive optics, holography and optical communications.

Multi-target object scattering imaging with intensity correlation of structured illumination

Imaging through scattering layers based on the optical memory effect (OME) concept has been widely investigated in recent years. Among many scattering scenarios, it is very important to recover hidden targets with proper spatial distribution in the scene where multiple targets out of the OME range exist. In this Letter, we put forward a method for multi-target object scattering imaging. With the help of intensity correlation between the structured illumination patterns and recorded speckle images, the relative position of all hidden targets can be obtained and the movement of the targets within the OME range can be tracked. We experimentally implement scattering imaging with 16 targets and the motion tracking of them. Our results present a significant advance in a large field of view scattering imaging with multiple targets.

Blind deconvolution in autocorrelation inversion for multiview light-sheet microscopy

Combining the information coming from multiview acquisitions is a problem of great interest in light-sheet microscopy. Aligning the views and increasing the resolution of their fusion can be challenging, especially if the setup is not fully calibrated. Here, we tackle these issues by proposing a new reconstruction method based on autocorrelation inversion that avoids alignment procedures. On top of this, we add a blind deconvolution step to improve the resolution of the final reconstruction. Our method permits us to achieve inherently aligned, highly resolved reconstructions while, at the same time, estimating the unknown point-spread function of the system. RESEARCH HIGHLIGHTS: We tackle the problem of multiview light-sheet deconvolution with a blind approach of autocorrelation inversion Our method recovers the object and PSF, requires no alignment and calibration, and enhances the reconstruction of the specimen.

High resolution optical projection tomography platform for multispectral imaging of the mouse gut

Optical projection tomography (OPT) is a powerful tool for three-dimensional imaging of mesoscopic biological samples with great use for biomedical phenotyping studies. We present a fluorescent OPT platform that enables direct visualization of biological specimens and processes at a centimeter scale with high spatial resolution, as well as fast data throughput and reconstruction. We demonstrate nearly isotropic sub-28 µm resolution over more than 60 mm3 after reconstruction of a single acquisition. Our setup is optimized for imaging the mouse gut at multiple wavelengths. Thanks to a new sample preparation protocol specifically developed for gut specimens, we can observe the spatial arrangement of the intestinal villi and the vasculature network of a 3-cm long healthy mouse gut. Besides the blood vessel network surrounding the gastrointestinal tract, we observe traces of vasculature at the villi ends close to the lumen. The combination of rapid acquisition and a large field of view with high spatial resolution in 3D mesoscopic imaging holds an invaluable potential for gastrointestinal pathology research.

Deconvolved Image Restoration From Auto-Correlations

The recovery of a real signal from its auto-correlation is a wide-spread problem in computational imaging, and it is equivalent to retrieve the phase linked to a given Fourier modulus. Image-deconvolution, on the other hand, is a funda- mental aspect to take into account when we aim at increasing the resolution of blurred signals. These problems are addressed separately in a large number of experimental situations, ranging from adaptive astronomy to optical microscopy. Here, instead, we tackle both at the same time, performing auto-correlation inversion while deconvolving the current object estimation. To this end, we propose a method based on I -divergence optimization, turning our formalism into an iterative scheme inspired by Bayesian-based approaches. We demonstrate the method by recovering sharp signals from blurred auto-correlations, regardless of whether the blurring acts in auto-correlation, object, or Fourier domain.

Non-invasive single-shot recovery of a point-spread function of a memory effect based scattering imaging system

Accessing the point-spread function (PSF) of a complex optical system is important for a variety of imaging applications. However, placing an invasive point source is often impractical, and estimating it blindly with multiple frames is slow and requires a complex nonlinear optimization. Here, we introduce a simple single-shot method to noninvasively recover the accurate PSF of an isoplanatic imaging system, in the context of multiple light scattering. Our approach is based on the reconstruction of any unknown sparse hidden object using the autocorrelation imaging technique, followed by a deconvolution with a blur kernel derived from the statistics of a speckle pattern. A deconvolution on the camera image then retrieves the accurate PSF of the system, enabling further imaging applications. We demonstrate numerically and experimentally the effectiveness of this approach compared to previous deconvolution techniques.

Three-dimensional bright-field microscopy with isotropic resolution based on multi-view acquisition and image fusion reconstruction

Optical Projection Tomography (OPT) is a powerful three-dimensional imaging technique used for the observation of millimeter-scaled biological samples, compatible with bright-field and fluorescence contrast. OPT is affected by spatially variant artifacts caused by the fact that light diffraction is not taken into account by the straight-light propagation models used for reconstruction. These artifacts hinder high-resolution imaging with OPT. In this work we show that, by using a multiview imaging approach, a 3D reconstruction of the bright-field contrast can be obtained without the diffraction artifacts typical of OPT, drastically reducing the amount of acquired data, compared to previously reported approaches. The method, purely based on bright-field contrast of the unstained sample, provides a comprehensive picture of the sample anatomy, as demonstrated in vivo on Arabidopsis thaliana and zebrafish embryos. Furthermore, this bright-field reconstruction can be implemented on practically any multi-view light-sheet fluorescence microscope without complex hardware modifications or calibrations, complementing the fluorescence information with tissue anatomy.